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609 KiB
Plaintext
9783 lines
609 KiB
Plaintext
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Contents Foreword
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Preface
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Acknowledgments
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Part I: The Basics of Option Greeks
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Chapter 1: The Basics
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Contractual Rights and Obligations
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ETFs, Indexes, and HOLDRs
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Strategies and At-Expiration Diagrams
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Chapter 2: Greek Philosophy
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Price vs. Value: How Traders Use Option-Pricing Models
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Delta
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Gamma
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Theta
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Vega
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Rho
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Where to Find Option Greeks
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Caveats with Regard to Online Greeks
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Thinking Greek
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Notes
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Chapter 3: Understanding Volatility
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Historical Volatility
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Implied Volatility
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Expected Volatility
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Implied Volatility and Direction
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Calculating Volatility Data
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Volatility Skew
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Note
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Chapter 4: Option-Specific Risk and Opportunity
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Long ATM Call
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Long OTM Call
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Long ITM Call
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Long ATM Put
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Finding the Right Risk
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It’s All About Volatility
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Options and the Fair Game
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Note
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Chapter 5: An Introduction to Volatility-Selling
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Strategies
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Profit Potential
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Chapter 6: Put-Call Parity and Synthetics
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Put-Call Parity Essentials
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American-Exercise Options
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Synthetic Stock
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Synthetic Stock Strategies
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Theoretical Value and the Interest Rate
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A Call Is a Put
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Note
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Chapter 7: Rho
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Rho and Interest Rates
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Rho and Time
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Considering Rho When Planning Trades
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Trading Rho
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Notes
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Chapter 8: Dividends and Option Pricing
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Dividend Basics
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Dividends and Option Pricing
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Dividends and Early Exercise
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Inputting Dividend Data into the Pricing Model
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Part II: Spreads
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Chapter 9: Vertical Spreads
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Vertical Spreads
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Verticals and Volatility
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The Interrelations of Credit Spreads and Debit Spreads
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Building a Box
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Verticals and Beyond
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Note
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Chapter 10: Wing Spreads
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Condors and Butterflies
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Taking Flight
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Keys to Success
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Greeks and Wing Spreads
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Directional Butterflies
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Constructing Trades to Maximize Profit
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The Retail Trader versus the Pro
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Notes
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Chapter 11: Calendar and Diagonal Spreads
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Calendar Spreads
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Trading Volatility Term Structure
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Diagonals
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The Strength of the Calendar
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Note
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Part III: Volatility
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Chapter 12: Delta-Neutral Trading
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Direction Neutral versus Direction Indifferent
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Delta Neutral
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Trading Implied Volatility
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Conclusions
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Chapter 13: Delta-Neutral Trading
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Gamma Scalping
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Art and Science
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Gamma, Theta, and Volatility
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Gamma Hedging
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Smileys and Frowns
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Chapter 14: Studying Volatility Charts
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Nine Volatility Chart Patterns
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Note
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Part IV: Advanced Option Trading
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Chapter 15: Straddles and Strangles
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Long Straddle
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Short Straddle
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Synthetic Straddles
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Long Strangle
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Short Strangle
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Note
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Chapter 16: Ratio Spreads and Complex Spreads
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Ratio Spreads
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How Market Makers Manage Delta-Neutral Positions
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Trading Skew
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When Delta Neutral Isn’t Direction Indifferent
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Managing Multiple-Class Risk
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Chapter 17: Putting the Greeks into Action
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Trading Option Greeks
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Choosing between Strategies
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Managing Trades
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The HAPI: The Hope and Pray Index
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Adjusting
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About the Author
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Index
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Since 1996, Bloomberg Press has published books for financial
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professionals on investing, economics, and policy affecting investors. Titles
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are written by leading practitioners and authorities, and have been translated
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into more than 20 languages.
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The Bloomberg Financial Series provides both core reference knowledge
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and actionable information for financial professionals. The books are
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written by experts familiar with the work flows, challenges, and demands of
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investment professionals who trade the markets, manage money, and
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analyze investments in their capacity of growing and protecting wealth,
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hedging risk, and generating revenue.
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For a list of available titles, please visit our web site at
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www.wiley.com/go/bloombergpress .
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Copyright © 2012 by Dan Passarelli. All rights reserved.
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Published by John Wiley & Sons, Inc., Hoboken, New Jersey.
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First edition was published in 2008 by Bloomberg Press.
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Published simultaneously in Canada.
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No part of this publication may be reproduced, stored in a retrieval system,
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or transmitted in any form or by any means, electronic, mechanical,
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photocopying, recording, scanning, or otherwise, except as permitted under
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Section 107 or 108 of the 1976 United States Copyright Act, without either
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the prior written permission of the Publisher, or authorization through
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payment of the appropriate per-copy fee to the Copyright Clearance Center,
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Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978)
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646-8600, or on the Web at www.copyright.com . Requests to the Publisher
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for permission should be addressed to the Permissions Department, John
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Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748-6011,
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fax (201) 748-6008, or online at www.wiley.com/go/permissions .
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Limit of Liability/Disclaimer of Warranty: While the publisher and author
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have used their best efforts in preparing this book, they make no
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representations or warranties with respect to the accuracy or completeness
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of the contents of this book and specifically disclaim any implied warranties
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of merchantability or fitness for a particular purpose. No warranty may be
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created or extended by sales representatives or written sales materials. The
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advice and strategies contained herein may not be suitable for your
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situation. You should consult with a professional where appropriate. Neither
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the publisher nor author shall be liable for any loss of profit or any other
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commercial damages, including but not limited to special, incidental,
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consequential, or other damages.
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Long-Term AnticiPation Securities® (LEAPS) is a registered trademark of
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the Chicago Board Options Exchange.
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Standard & Poor’s 500® (S&P 500) and Standard & Poor’s Depository
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Receipts™ (SPDRs) are registered trademarks of the McGraw-Hill
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Companies, Inc.
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Power Shares QQQ™ is a registered trademark of Invesco PowerShares
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Capital Management LLC.
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NASDAQ-100 Index® is a registered trademark of The NASDAQ Stock
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Market, Inc.
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For general information on our other products and services or for technical
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support, please contact our Customer Care Department within the United
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States at (800) 762-2974, outside the United States at (317) 572-3993 or fax
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(317) 572-4002.
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Wiley also publishes its books in a variety of electronic formats. Some
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content that appears in print may not be available in electronic books. For
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more information about Wiley products, visit our web site at
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www.wiley.com .
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Library of Congress Cataloging-in-Publication Data :
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Passarelli, Dan, 1971-
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Trading options Greeks : how time, volatility, and other pricing factors
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drive profits / Dan Passarelli. – 2nd ed.
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p. cm. – (Bloomberg financial series)
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Includes index.
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ISBN 978-1-118-13316-3 (cloth); ISBN 978-1-118-22512-7 (ebk); ISBN
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978-1-118-26322-8 (ebk); ISBN 978-1-118-23861-5 (ebk)
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1. Options (Finance) 2. Stock options. 3. Derivative securities. I. Title.
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HG6024.A3P36 2012
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332.64′53—dc23
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2012019462
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This book is dedicated to Kathleen, Sam, and Isabel. I wouldn’t trade them
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for all the money in the world .
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Disclaimer
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This book is intended to be educational in nature, both theoretically and
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practically. It is meant to generally explore the factors that influence option
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prices so that the reader may gain an understanding of how options work in
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the real world. This book does not prescribe a specific trading system or
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method. This book makes no guarantees.
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||
Any strategies discussed, including examples using actual securities and
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price data, are strictly for illustrative and educational purposes only and are
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||
not to be construed as an endorsement, recommendation, or solicitation to
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||
buy or sell securities. Examples may or may not be based on factual or
|
||
historical data.
|
||
In order to simplify the computations, examples may not include
|
||
commissions, fees, margin, interest, taxes, or other transaction costs.
|
||
Commissions and other costs will impact the outcome of all stock and
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||
options transactions and must be considered prior to entering into any
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||
transactions. Investors should consult their tax adviser about potential tax
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||
consequences. Past performance is not a guarantee of future results.
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||
Options involve risks and are not suitable for everyone. While much of
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||
this book focuses on the risks involved in option trading, there are market
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||
situations and scenarios that involve unique risks that are not discussed.
|
||
Prior to buying or selling an option, a person should read Characteristics
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||
and Risks of Standardized Options (ODD) . Copies of the ODD are
|
||
available from your broker, by calling 1-888-OPTIONS, or from The
|
||
Options Clearing Corporation, One North Wacker Drive, Chicago, Illinois
|
||
60606.
|
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Foreword
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The past several years have brought about a resurgence in market volatility
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and options volume unlike anything that has been seen since the close of the
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twentieth century. As markets have become more interdependent,
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interrelated, and international, the U.S. listed option markets have solidified
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||
their place as the most liquid and transparent venue for risk management
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||
and hedging activities of the world’s largest economy. Technology,
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||
competition, innovation, and reliability have become the hallmarks of the
|
||
industry, and our customer base has benefited tremendously from this
|
||
ongoing evolution.
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||
However, these advances can be properly tapped only when the users of
|
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the product continue to expand their knowledge of the options product and
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its unique features. Education has always been the driver of growth in our
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business, and it will be the steward of the next generation of options traders.
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Dan Passarelli’s new and updated book Trading Option Greeks is a
|
||
necessity for customers and traders alike to ensure that they possess the
|
||
knowledge to succeed and attain their objectives in the high-speed, highly
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||
technical arena that the options market has become.
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||
The retail trader of the past has given way to a new retail trader of the
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present—one with an increased level of technology, support, capital
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||
treatment, and product selection. The impact of the staggering growth in
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such products as the CBOE Holdings’ VIX options and futures, and the
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||
literally dozens of other products tied to it, have made the volatility asset
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class a new, unique, and permanent pillar of today’s option markets.
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Dan’s updated book continues his mission of supporting, preparing, and
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reinforcing the trader’s understanding of pricing, volatility, market
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terminology, and strategy, in a way that few other books have been able.
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Using a perspective forged from years as an options market maker,
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professional trader, and customer, Dan has once again provided a resource
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for those who wish to know best how the option markets behave today, and
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how they are likely to continue to behave in the future. It is important to
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understand not only what happens in the options space, but also why it
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happens. This book is intended to provide those answers. I wish you all the
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best in your trading!
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William J. Brodsky
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Chairman and CEO Chicago Board Options Exchange
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Preface
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I’ve always been fascinated by trading. When I was young, I’d see traders
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on television, in their brightly colored jackets, shouting on the seemingly
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chaotic trading floor, and I’d marvel at them. What a wonderful job that
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must be! These traders seemed to me to be very different from the rest of
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us. It’s all so very esoteric.
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It is easy to assume that professional traders have closely kept secrets to
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their ways of trading—something that secures success in trading for them,
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||
but is out of reach for everyone else. In fact, nothing could be further from
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||
the truth. If there are any “secrets” of professional traders, this book will
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||
expose them.
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True enough, in years past there have been some barriers to entry to
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trading success that did indeed make it difficult for nonprofessionals to
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||
succeed. For example, commissions, bid-ask spreads, margin requirements,
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||
and information flow all favored the professional trader. Now, these barriers
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are gone. Competition among brokers and exchanges—as well as the
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ubiquity of information as propagated on the Internet—has torn down those
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walls. The only barrier left between the Average Joe and the options pro is
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that of knowledge. Those who have it will succeed; those who do not will
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fail.
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To be sure, the knowledge held by successful traders is not that of what
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will happen in the future; it is the knowledge of how to manage the
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uncertainty. No matter what our instincts tell us, we do not know what will
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happen in the future with regard to the market. As Socrates put it, “The only
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true wisdom is in knowing you know nothing.” The masters of option
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trading are masters of managing the risk associated with what they don’t
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know—the risk of uncertainty.
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As an instructor, I’ve talked to many traders who were new to options
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who told me, “I made a trade based on what I thought was going to happen.
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I was right, but my position lost money!” Choosing the right strategy makes
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all the difference when it comes to mastery of risk management and
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ultimate trading success. Knowing which option strategy is the right
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strategy for a given situation comes with knowledge and experience.
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All option strategies are differentiated by their unique risk characteristics.
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Some are more sensitive to directional movement of the underlying asset
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than others; some are more affected by time passing than others. The exact
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exposure positions have to these market influences determines the success
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of individual trades and, indeed, the long-term success of the trader who
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knows how to exploit these risk characteristics. These option-value
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sensitivities can be controlled when a trader understands the option greeks.
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Option greeks are metrics used to measure an option’s sensitivity to
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influences on its price. This book will provide the reader with an
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understanding of these metrics, to help the reader truly master the risk of
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uncertainty associated with option trading.
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Successful traders strive to create option positions with risk-reward
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profiles that benefit them the most in a given situation. A trader’s objectives
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will dictate the right strategy for the right situation. Traders can tailor a
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position to fit a specific forecast with respect to the time horizon; the degree
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of bullishness, bearishness, neutrality, or volatility in the underlying stock;
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and the desired amount of leverage. Furthermore, they can exploit
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opportunities unique to options. They can trade option greeks. This opens
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the door to many new opportunities.
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A New Direction
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Traders, both professional and retail, need ways to act on their forecasts
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without the constraints of convention. “Get long, or do nothing” is no
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longer a viable business model for people active in the market. “Up is good;
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down is bad” is burned into traders’ minds from the beginning of their
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market education. This concept has its place in the world of investing, but
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becoming an active trader in the option market requires thinking in a new
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direction.
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Market makers and other expert option traders look at the market
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differently from other traders. One fundamental difference is that these
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traders trade all four directions: up, down, sideways, and volatile.
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Trading Strategies
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Buying stock is a trading strategy that most people understand. In practical
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terms, traders who buy stock are generally not concerned with the literal
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ownership stake in a corporation, just the opportunity to profit if the stock
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rises. Although it’s important for traders to understand that the price of a
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stock is largely tied to the success or failure of the corporation, it’s essential
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to keep in mind exactly what the objective tends to be for trading a stock: to
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profit from changes in its price. A bullish position can also be taken in the
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options market. The most basic example is buying a call.
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A bearish position can be taken by trading stock or options, as well. If
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traders expect the value of a stock they own to fall, they will sell the stock.
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This eliminates the risk of losses from the stock’s falling. If the traders do
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not own the stock that they think will decline, they can take a more active
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stance and short it. The short-seller borrows the stock from a party that
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owns it and then sells the borrowed shares to another party. The goal of
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selling stock short is to later repurchase the shares at a lower price before
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returning the stock to its owner. It is simply reversing the order of “buy
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low/sell high.” The risk is that the stock rises and shares have to be bought
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at a higher price than that at which they were sold. Although shorting stock
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can lead to profits when the market cooperates, in the options market, there
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are alternative ways to profit from falling prices. The most basic example is
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buying a put.
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A trader can use options to take a bullish or bearish position, given a
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directional forecast. Sideways, nontrending stocks and their antithesis,
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volatile stocks, can be traded as well. In the later market conditions, profit
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or loss can be independent of whether the stock rises or falls. Opportunity
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in option trading is not necessarily black and white—not necessarily up and
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down. Option trading is nonlinear. Consequently, more opportunities can be
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exploited by trading options than by trading stock.
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Option traders must consider the time period in question, the volatility
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expected during this period, interest rates, and dividends. Along with the
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stock price, these factors make up the dynamic components of an option’s
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value. These individual factors can be isolated, measured, and exploited.
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Incremental changes in any of these elements as measured by option greeks
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provide opportunity for option traders. Because of these other influences,
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direction is not the only tradable element of a forecast. Time, volatility,
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interest rates—these can all be traded using option greeks. These factors
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and more will all be discussed at great length throughout this book.
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This Second Edition of Trading
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Option Greeks
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This book addresses the complex price behavior of options by discussing
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option greeks from both a theoretical and a practical standpoint. There is
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some tactical discussion throughout, although the objective of this book is
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to provide education to the reader. This book is meant to be less a how-to
|
||
manual than a how-come tutorial.
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||
This informative guide will give the retail trader a look inside the mind of
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a professional trader. It will help the professional trader better understand
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the essential concepts of his craft. Even the novice trader will be able to
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apply these concepts to basic options strategies. Comprehensive knowledge
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of the greeks can help traders to avoid common pitfalls and increase profit
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potential.
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Much of this book is broken down into a discussion of individual
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strategies. Although the nuances of each specific strategy are not relevant,
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presenting the material this way allows for a discussion of very specific
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situations in which greeks come into play. Many of the concepts discussed
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in a section on one option strategy can be applied to other option strategies.
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As in the first edition of Trading Option Greeks , Chapter 1 discusses
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basic option concepts and definitions. It was written to be a review of the
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basics for the intermediate to advanced trader. For newcomers, it’s essential
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to understand these concepts before moving forward.
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||
A detailed explanation of option greeks begins in Chapter 2. Be sure to
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leave a bookmark in this chapter, as you will flip to it several times while
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reading the rest of the book and while studying the market thereafter.
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Chapter 3 introduces volatility. The same bookmark advice can be applied
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here, as well. Chapters 4 and 5 explore the minds of option traders. What
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are the risks they look out for? What are the opportunities they seek? These
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chapters also discuss direction-neutral and direction-indifferent trading. The
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remaining chapters take the reader from concept to application, discussing
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the strategies for nonlinear trading and the tactical considerations of a
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successful options trader.
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New material in this edition includes updated examples, with more
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current price information throughout many of the chapters. More detailed
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||
discussions are also included to give the reader a deeper understanding of
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important topics. For example, Chapter 8 has a more elaborate explanation
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||
of the effect of dividends on option prices. Chapter 17 of this edition has
|
||
new material on strategy selection, position management, and adjusting, not
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||
featured in the first edition of the book.
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Acknowledgments
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A book like Trading Option Greeks is truly a collaboration of the efforts of
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many people. In my years as a trader, I had many teachers in the School of
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Hard Knocks. I have had the support of friends and family during the trials
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and tribulations throughout my trading career, as well as during the time
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spent writing this book, both the first edition and now this second edition.
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Surely, there are hundreds of people whose influences contributed to the
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||
creation of this book, but there are a few in particular to whom I’d like to
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||
give special thanks.
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I’d like to give a very special thanks to my mentor and friend from the
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CBOE’s Options Institute, Jim Bittman. Without his help this book would
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not have been written. Thanks to Marty Kearney and Joe Troccolo for
|
||
looking over the manuscript. Their input was invaluable. Thanks to Debra
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Peters for her help during my career at the Options Institute. Thanks to
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Steve Fossett and Bob Kirkland for believing in me. Thanks to the staff at
|
||
Bloomberg Press, especially Stephen Isaacs and Kevin Commins. Thanks to
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my friends at the Chicago Board Options Exchange, the Options Industry
|
||
Council, and the CME group. Thanks to John Kmiecik for his diligent
|
||
content editing. Thanks to those who contribute to sharing option ideas on
|
||
my website, markettaker.com . Thanks to my wife, Kathleen, who has been
|
||
more patient and supportive than anyone could reasonably ask for. And
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||
thanks, especially, to my students and those of you reading this book.
|
||
PART I
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||
The Basics of Option Greeks
|
||
CHAPTER 1
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||
The Basics
|
||
To understand how options work, one needs first to understand what an
|
||
option is. An option is a contract that gives its owner the right to buy or the
|
||
right to sell a fixed quantity of an underlying security at a specific price
|
||
within a certain time constraint. There are two types of options: calls and
|
||
puts. A call gives the owner of the option the right to buy the underlying
|
||
security. A put gives the owner of the option the right to sell the underlying
|
||
security. As in any transaction, there are two parties to an option contract—
|
||
a buyer and a seller.
|
||
Contractual Rights and Obligations
|
||
The option buyer is the party who owns the right inherent in the contract.
|
||
The buyer is referred to as having a long position and may also be called the
|
||
holder, or owner, of the option. The right doesn’t last forever. At some point
|
||
the option will expire. At expiration, the owner may exercise the right or, if
|
||
the option has no value to the holder, let it expire without exercising it. But
|
||
he need not hold the option until expiration. Options are transferable—they
|
||
can be traded intraday in much the same way as stock is traded. Because it’s
|
||
uncertain what the underlying stock price of the option will be at expiration,
|
||
much of the time this right has value before it expires. The uncertainty of
|
||
stock prices, after all, is the raison d’être of the option market.
|
||
A long position in an option contract, however, is fundamentally different
|
||
from a long position in a stock. Owning corporate stock affords the
|
||
shareholder ownership rights, which may include the right to vote in
|
||
corporate affairs and the right to receive dividends. Owning an option
|
||
represents strictly the right either to buy the stock or to sell it, depending on
|
||
whether it’s a call or a put. Option holders do not receive dividends that
|
||
would be paid to the shareholders of the underlying stock, nor do they have
|
||
voting rights. The corporation has no knowledge of the parties to the option
|
||
contract. The contract is created by the buyer and seller of the option and
|
||
made available by being listed on an exchange.
|
||
The party to the contract who is referred to as the option seller, also called
|
||
the option writer, has a short position in the option. Instead of having a right
|
||
to take a position in the underlying stock, as the buyer does, the seller
|
||
incurs an obligation to potentially either buy or sell the stock. When a trader
|
||
who is long an option exercises, a trader with a short position gets assigned
|
||
. Assignment means the trader with the short option position is called on to
|
||
fulfill the obligation that was established when the contract was sold.
|
||
Shorting an option is fundamentally different from shorting a stock.
|
||
Corporations have a quantifiable number of outstanding shares available for
|
||
trading, which must be borrowed to create a short position, but establishing
|
||
a short position in an option does not require borrowing; the contract is
|
||
simply created. The strategy of shorting stock is implemented statistically
|
||
far less frequently than simply buying stock, but that is not at all the case
|
||
with options. For every open long-option contract, there is an open short-
|
||
option contract—they are equally common.
|
||
Opening and Closing
|
||
Traders’ option orders are either opening or closing transactions. When
|
||
traders with no position in a particular option buy the option, they buy to
|
||
open. If, in the future, the traders wish to eliminate the position by selling
|
||
the option they own, the traders enter a sell to close order—they are closing
|
||
the position. Likewise, if traders with no position in a particular option want
|
||
to sell an option, thereby creating a short position, the traders execute a sell-
|
||
to-open transaction. When the traders cover the short position by buying
|
||
back the option, the traders enter a buy-to-close order.
|
||
Open Interest and Volume
|
||
Traders use many types of market data to make trading decisions. Two
|
||
items that are often studied but sometimes misunderstood are volume and
|
||
open interest. Volume, as the name implies, is the total number of contracts
|
||
traded during a time period. Often, volume is stated on a one-day basis, but
|
||
could be stated per week, month, year, or otherwise. Once a new period
|
||
(day) begins, volume begins again at zero. Open interest is the number of
|
||
contracts that have been created and remain outstanding. Open interest is a
|
||
running total.
|
||
When an option is first listed, there are no open contracts. If Trader A
|
||
opens a long position in a newly listed option by buying a one-lot, or one
|
||
contract, from Trader B, who by selling is also opening a position, a
|
||
contract is created. One contract traded, so the volume is one. Since both
|
||
parties opened a position and one contract was created, the open interest in
|
||
this particular option is one contract as well. If, later that day, Trader B
|
||
closes his short position by buying one contract from Trader C, who had no
|
||
position to start with, the volume is now two contracts for that day, but open
|
||
interest is still one. Only one contract exists; it was traded twice. If the next
|
||
day, Trader C buys her contract back from Trader A, that day’s volume is
|
||
one and the open interest is now zero.
|
||
The Options Clearing Corporation
|
||
Remember when Wimpy would tell Popeye, “I’ll gladly pay you Tuesday
|
||
for a hamburger today.” Did Popeye ever get paid for those burgers? In a
|
||
contract, it’s very important for each party to hold up his end of the bargain
|
||
—especially when there is money at stake. How does a trader know the
|
||
party on the other side of an option contract will in fact do that? That’s
|
||
where the Options Clearing Corporation (OCC) comes into play.
|
||
The OCC ultimately guarantees every options trade. In 2010, that was
|
||
almost 3.9 billion listed-options contracts. The OCC accomplishes this
|
||
through many clearing members. Here’s how it works: When Trader X buys
|
||
an option through a broker, the broker submits the trade information to its
|
||
clearing firm. The trader on the other side of this transaction, Trader Y, who
|
||
is probably a market maker, submits the trade to his clearing firm. The two
|
||
clearing firms (one representing Trader X’s buy, the other representing
|
||
Trader Y’s sell) each submit the trade information to the OCC, which
|
||
“matches up” the trade.
|
||
If Trader Y buys back the option to close the position, how does that
|
||
affect Trader X if he wants to exercise it? It doesn’t. The OCC, acting as an
|
||
intermediary, assigns one of its clearing members with a customer that is
|
||
short the option in question to deliver the stock to Trader X’s clearing firm,
|
||
which in turn delivers the stock to Trader X. The clearing member then
|
||
assigns one of its customers who is short the option. The clearing member
|
||
will assign the trader either randomly or first in, first out. Effectively, the
|
||
OCC is the ultimate counterparty to both the exercise and the assignment.
|
||
Standardized Contracts
|
||
Exchange-listed options contracts are standardized, meaning the terms of
|
||
the contract, or the contract specifications, conform to a customary
|
||
structure. Standardization makes the terms of the contracts intuitive to the
|
||
experienced user.
|
||
To understand the contract specifications in a typical equity option,
|
||
consider an example:
|
||
Buy 1 IBM December 170 call at 5.00
|
||
Quantity
|
||
In this example, one contract is being purchased. More could have been
|
||
purchased, but not less—options cannot be traded in fractional units.
|
||
Option Series, Option Class, and Contract Size
|
||
All calls or puts of the same class, the same expiration month, and the same
|
||
strike price are called an option series . For example, the IBM December
|
||
170 calls are a series. Options series are displayed in an option chain on an
|
||
online broker’s user interface. An option chain is a full or partial list of the
|
||
options that are listed on an underlying.
|
||
Option class means a group of options that represent the same underlying.
|
||
Here, the option class is denoted by the symbol IBM—the contract
|
||
represents rights on International Business Machines Corp. (IBM) shares.
|
||
Buying one contract usually gives the holder the right to buy or to sell 100
|
||
shares of the underlying stock. This number is referred to as contract size .
|
||
Though this is usually the case, there are times when the contract size is
|
||
something other than 100 shares of a stock. This situation may occur after
|
||
certain types of stock splits, spin-offs, or stock dividends, for example. In
|
||
the minority of cases in which the one contract represents rights on
|
||
something besides 100 shares, there may be more than one class of options
|
||
listed on a stock.
|
||
A fairly unusual example was presented by the Ford Motor Company
|
||
options in the summer of 2000. In June 2000, Ford spun off Visteon
|
||
Corporation. Then, in August 2000, Ford offered shareholders a choice of
|
||
converting their shares into (a) new shares of Ford plus $20 cash per share,
|
||
(b) new Ford stock plus fractional shares with an aggregate value of $20, or
|
||
(c) new Ford stock plus a combination of more new Ford stock and cash.
|
||
There were three classes of options listed on Ford after both of these
|
||
changes: F represented 100 shares of the new Ford stock; XFO represented
|
||
100 shares of Ford plus $20 per share ($2,000) plus cash in lieu of $1.24;
|
||
and FOD represented 100 shares of new Ford, 13 shares of Visteon, and
|
||
$2,001.24.
|
||
Sometimes these changes can get complicated. If there is ever a question
|
||
as to what the underlying is for an option class, the authority is the OCC. A
|
||
lot of time, money, and stress can be saved by calling the OCC at 888-
|
||
OPTIONS and clarifying the matter.
|
||
Expiration Month
|
||
Options expire on the Saturday following the third Friday of the stated
|
||
month, which in this case is December. The final trading day for an option
|
||
is commonly the day before expiration—here, the third Friday of
|
||
December. There are usually at least four months listed for trading on an
|
||
option class. There may be a total of six months if Long-Term Equity
|
||
AnticiPation Securities® or LEAPS® are listed on the class. LEAPS can have
|
||
one year to about two-and-a-half years until expiration. Some underlyings
|
||
have one-week options called WeeklysSM listed on them.
|
||
Strike Price
|
||
The price at which the option holder owns the right to buy or to sell the
|
||
underlying is called the strike price, or exercise price. In this example, the
|
||
holder owns the right to buy the stock at $170 per share. There is method to
|
||
the madness regarding how strike prices are listed. Strike prices are
|
||
generally listed in $1, $2.50, $5, or $10 increments, depending on the value
|
||
of the strikes and the liquidity of the options.
|
||
The relationship of the strike price to the stock price is important in
|
||
pricing options. For calls, if the stock price is above the strike price, the call
|
||
is in-the-money (ITM). If the stock and the strike prices are close, the call is
|
||
at-the-money (ATM). If the stock price is below the strike price the call is
|
||
out-of-the-money (OTM). This relationship is just the opposite for puts. If
|
||
the stock price is below the strike price, the put is in-the-money. If the stock
|
||
price and the strike price are about the same, the put is at-the-money. And,
|
||
if the stock price is above the put strike, it is out-of-the-money.
|
||
Option Type
|
||
There are two types of options: calls and puts. Calls give the holder the
|
||
right to buy the underlying and the writer the obligation to sell the
|
||
underlying. Puts give the holder the right to sell the underlying and the
|
||
writer the obligation to buy the underlying.
|
||
Premium
|
||
The price of an option is called its premium. The premium of this option is
|
||
$5. Like stock prices, option premiums are stated in dollars and cents per
|
||
share. Since the option represents 100 shares of IBM, the buyer of this
|
||
option will pay $500 when the transaction occurs. Certain types of spreads
|
||
may be quoted in fractions of a penny.
|
||
An option’s premium is made up of two parts: intrinsic value and time
|
||
value. Intrinsic value is the amount by which the option is in-the-money.
|
||
For example, if IBM stock were trading at 171.30, this 170-strike call
|
||
would be in-the-money by 1.30. It has 1.30 of intrinsic value. The
|
||
remaining 3.70 of its $5 premium would be time value.
|
||
Options that are out-of-the-money have no intrinsic value. Their values
|
||
consist only of time premium. Sometimes options have no time value left.
|
||
Options that consist of only intrinsic value are trading at what traders call
|
||
parity . Time value is sometimes called premium over parity .
|
||
Exercise Style
|
||
One contract specification that is not specifically shown here is the exercise
|
||
style. There are two main exercise styles: American and European.
|
||
American-exercise options can be exercised, and therefore assigned,
|
||
anytime after the contract is entered into until either the trader closes the
|
||
position or it expires. European-exercise options can be exercised and
|
||
assigned only at expiration. Exchange-listed equity options are all
|
||
American-exercise style. Other kinds of options are commonly European
|
||
exercise. Whether an option is American or European has nothing to with
|
||
the country in which it’s listed.
|
||
ETFs, Indexes, and HOLDRs
|
||
So far, we’ve focused on equity options—options on individual stocks. But
|
||
investors have other choices for trading securities options. Options on
|
||
baskets of stocks can be traded, too. This can be accomplished using
|
||
options on exchange-traded funds (ETFs), index options, or options on
|
||
holding company depositary receipts (HOLDRs).
|
||
ETF Options
|
||
Exchange-traded funds are vehicles that represent ownership in a fund or
|
||
investment trust. This fund is made up of a basket of an underlying index’s
|
||
securities—usually equities. The contract specifications of ETF options are
|
||
similar to those of equity options. Let’s look at an example.
|
||
One actively traded optionable ETF is the Standard & Poor’s Depositary
|
||
Receipts (SPDRs or Spiders). Spider shares and options trade under the
|
||
symbol SPY. Exercising one SPY call gives the exerciser a long position of
|
||
100 shares of Spiders at the strike price of the option. Expiration for ETF
|
||
options typically falls on the same day as for equity options—the Saturday
|
||
following the third Friday of the month. The last trading day is the Friday
|
||
before. ETF options are American exercise. Traders of ETFs should be
|
||
aware of the relationship between the price of the ETF shares and the value
|
||
of the underlying index. For example, the stated value of the Spiders is
|
||
about one tenth the stated value of the S&P 500. The PowerShares QQQ
|
||
ETF, representing the Nasdaq 100, is about one fortieth the stated value of
|
||
the Nasdaq 100.
|
||
Index Options
|
||
Trading options on the Spiders ETF is a convenient way to trade the
|
||
Standard & Poor’s (S&P) 500. But it’s not the only way. There are other
|
||
option contracts listed on the S&P 500. The SPX is one of the major ones.
|
||
The SPX is an index option contract. There are some very important
|
||
differences between ETF options like SPY and index options like SPX.
|
||
The first difference is the underlying. The underlying for ETF options is
|
||
100 shares of the ETF. The underlying for index options is the numerical
|
||
value of the index. So if the S&P 500 is at 1303.50, the underlying for SPX
|
||
options is 1303.50. When an SPX call option is exercised, instead of getting
|
||
100 shares of something, the exerciser gets the ITM cash value of the
|
||
option times $100. Again, with SPX at 1303.50, if a 1300 call is exercised,
|
||
the exerciser gets $350—that’s 1303.50 minus 1300, times $100. This is
|
||
called cash settlement .
|
||
Many index options are European, which means no early exercise. At
|
||
expiration, any long ITM options in a trader’s inventory result in an account
|
||
credit; any short ITMs result in a debit of the ITM value times $100. The
|
||
settlement process for determining whether a European-style index option is
|
||
in-the-money at expiration is a little different, too. Often, these indexes are
|
||
a.m. settled. A.m.-settled index options will have actual expiration on the
|
||
conventional Saturday following the third Friday of the month. But the final
|
||
trading day is the Thursday before the expiration day. The final settlement
|
||
value of the index is determined by the opening prices of the components of
|
||
the index on Friday morning.
|
||
HOLDR Options
|
||
Like ETFs, holding company depositary receipts also represent ownership
|
||
in a basket of stocks. The main difference is that investors owning
|
||
HOLDRs retain the ownership rights of the individual stocks in the fund,
|
||
such as the right to vote shares and the right to receive dividends. Options
|
||
on HOLDRs, for all intents and purposes, function much like options on
|
||
ETFs.
|
||
Strategies and At-Expiration
|
||
Diagrams
|
||
One of the great strengths of options is that there are so many different
|
||
ways to use them. There are simple, straightforward strategies like buying a
|
||
call. And there are complex spreads with creative names like jelly roll, guts,
|
||
and iron butterfly. A spread is a strategy that involves combining an option
|
||
with one or more other options or stock. Each component of the spread is
|
||
referred to as a leg. Each spread has its own unique risk and reward
|
||
characteristics that make it appropriate for certain market outlooks.
|
||
Throughout this book, many different spreads will be discussed in depth.
|
||
For now, it’s important to understand that all spreads are made up of a
|
||
combination of four basic option positions: buy call, sell call, buy put, and
|
||
sell put. Understanding complex option strategies requires understanding
|
||
these basic positions and their common, practical uses. When learning
|
||
options, it’s helpful to see what the option’s payout is if it is held until
|
||
expiration.
|
||
Buy Call
|
||
Why buy the right to buy the stock when you can simply buy the stock? All
|
||
option strategies have trade-offs, and the long call is no different. Whether
|
||
the stock or the call is preferable depends greatly on the trader’s forecast
|
||
and motivations.
|
||
Consider a long call example:
|
||
Buy 1 INTC June 22.50 call at 0.85.
|
||
In this example, a trader is bullish on Intel (INTC). He believes Intel will
|
||
rise at least 20 percent, from $22.25 per share to around $27 by June
|
||
expiration, about two months from now. He is concerned, however, about
|
||
downside risk and wants to limit his exposure. Instead of buying 100 shares
|
||
of Intel at $22.25—a total investment of $2,225—the trader buys 1 INTC
|
||
June 22.50 call at 0.85, for a total of $85.
|
||
The trader is paying 0.85 for the right to buy 100 shares of Intel at $22.50
|
||
per share. If Intel is trading below the strike price of $22.50 at expiration,
|
||
the call will expire and the total premium of 0.85 will be lost. Why? The
|
||
trader will not exercise the right to buy the stock at a $22.50 if he can buy it
|
||
cheaper in the market. Therefore, if Intel is below $22.50 at expiration, this
|
||
call will expire with no value.
|
||
However, if the stock is trading above the strike price at expiration, the
|
||
call can be exercised, in which case the trader may purchase the stock
|
||
below its trading price. Here, the call has value to the trader. The higher the
|
||
stock, the more the call is worth. For the trade to be profitable, at expiration
|
||
the stock must be trading above the trader’s break-even price. The break-
|
||
even price for a long call is the strike price plus the premium paid—in this
|
||
example, $23.35 per share. The point here is that if the call is exercised, the
|
||
effective purchase price of the stock upon exercise is $23.35. The stock is
|
||
literally bought at the strike price, which is $22.50, but the premium of 0.85
|
||
that the trader has paid must be taken into account. Exhibit 1.1 illustrates
|
||
this example.
|
||
EXHIBIT 1.1 Long Intel call.
|
||
Exhibit 1.1 is an at-expiration diagram for the Intel 22.50 call. It shows
|
||
the profit and loss, or P&(L), of the option if it is held until expiration. The
|
||
X-axis represents the prices at which INTC could be trading at expiration.
|
||
The Y-axis represents the associated profit or loss on the position. The at-
|
||
expiration diagram of any long call position will always have this same
|
||
hockey-stick shape, regardless of the stock or strike. There is always a limit
|
||
of loss, represented by the horizontal line, which in this case is drawn at
|
||
−0.85. And there is always a line extending upward and to the right, which
|
||
represents effectively a long stock position stemming from the strike.
|
||
The trade-offs between a long stock position and a long call position are
|
||
shown in Exhibit 1.2 .
|
||
EXHIBIT 1.2 Long Intel call vs. long Intel stock.
|
||
The thin dotted line represents owning 100 shares of Intel at $22.25.
|
||
Profits are unlimited, but the risk is substantial—the stock can go to zero.
|
||
Herein lies the trade-off. The long call has unlimited profit potential with
|
||
limited risk. Whenever an option is purchased, the most that can be lost is
|
||
the premium paid for the option. But the benefit of reduced risk comes at a
|
||
cost. If the stock is above the strike at expiration, the call will always
|
||
underperform the stock by the amount of the premium.
|
||
Because of this trade-off, conservative traders will sometimes buy a call
|
||
rather than the associated stock and sometimes buy the stock rather than the
|
||
call. Buying a call can be considered more conservative when the volatility
|
||
of the stock is expected to rise. Traders are willing to risk a comparatively
|
||
small premium when a large price decline is feared possible. Instead, in an
|
||
interest-bearing vehicle, they harbor the capital that would otherwise have
|
||
been used to purchase the stock. The cost of this protection is acceptable to
|
||
the trader if high-enough price advances are anticipated. In terms of
|
||
percentage, much higher returns and losses are possible with the long call.
|
||
If the stock is trading at $27 at expiration, as the trader in this example
|
||
expected, the trader reaps a 429 percent profit on the $0.85 investment
|
||
([$27 − 23.35] / $0.85). If Intel is below the strike price at expiration, the
|
||
trader loses 100 percent.
|
||
This makes call buying an excellent speculative alternative. Those willing
|
||
to accept bigger risk can further increase returns by purchasing more calls.
|
||
In this example, around 26 Intel calls—representing the rights on 2,600
|
||
shares—can be purchased at 85 cents for the cost of 100 shares at $22.25.
|
||
This is the kind of leverage that allows for either a lower cash outlay than
|
||
buying the stock—reducing risk—or the same cash outlay as buying the
|
||
stock but with much greater exposure—creating risk in pursuit of higher
|
||
returns.
|
||
Sell Call
|
||
Selling a call creates the obligation to sell the stock at the strike price. Why
|
||
is a trader willing to accept this obligation? The answer is option premium.
|
||
If the position is held until expiration without getting assigned, the entire
|
||
premium represents a profit for the trader. If assignment occurs, the trader
|
||
will be obliged to sell stock at the strike price. If the trader does not have a
|
||
long position in the underlying stock (a naked call), a short stock position
|
||
will be created. Otherwise, if stock is owned (a covered call), that stock is
|
||
sold. Whether the trader has a profit or a loss depends on the movement of
|
||
the stock price and how the short call position was constructed.
|
||
Consider a naked call example:
|
||
Sell 1 TGT October 50 call at 1.45
|
||
In this example, Target Corporation (TGT) is trading at $49.42. A trader,
|
||
Sam, believes Target will continue to be trading below $50 by October
|
||
expiration, about two months from now. Sam sells 1 Target two-month 50
|
||
call at 1.45, opening a short position in that series. Exhibit 1.3 will help
|
||
explain the expected payout of this naked call position if it is held until
|
||
expiration.
|
||
EXHIBIT 1.3 Naked Target call.
|
||
If TGT is trading below the exercise price of 50, the call will expire
|
||
worthless. Sam keeps the 1.45 premium, and the obligation to sell the stock
|
||
ceases to exist. If Target is trading above the strike price, the call will be in-
|
||
the-money. The higher the stock is above the strike price, the more intrinsic
|
||
value the call will have. As a seller, Sam wants the call to have little or no
|
||
intrinsic value at expiration. If the stock is below the break-even price at
|
||
expiration, Sam will still have a profit. Here, the break-even price is $51.45
|
||
—the strike price plus the call premium. Above the break-even, Sam has a
|
||
loss. Since stock prices can rise to infinity (although, for the record, I have
|
||
never seen this happen), the naked call position has unlimited risk of loss.
|
||
Because a short stock position may be created, a naked call position must
|
||
be done in a margin account. For retail traders, many brokerage firms
|
||
require different levels of approval for different types of option strategies.
|
||
Because the naked call position has unlimited risk, establishing it will
|
||
generally require the highest level of approval—and a high margin
|
||
requirement.
|
||
Another tactical consideration is what Sam’s objective was when he
|
||
entered the trade. His goal was to profit from the stock’s being below $50
|
||
during this two-month period—not to short the stock. Because equity
|
||
options are American exercise and can be exercised/assigned any time from
|
||
the moment the call is sold until expiration, a short stock position cannot
|
||
always be avoided. If assigned, the short stock position will extend Sam’s
|
||
period of risk—because stock doesn’t expire. Here, he will pay one
|
||
commission shorting the stock when assignment occurs and one more when
|
||
he buys back the unwanted position. Many traders choose to close the naked
|
||
call position before expiration rather than risk assignment.
|
||
It is important to understand the fundamental difference between buying
|
||
calls and selling calls. Buying a call option offers limited risk and unlimited
|
||
reward. Selling a naked call option, however, has limited reward—the call
|
||
premium—and unlimited risk. This naked call position is not so much
|
||
bearish as not bullish . If Sam thought the stock was going to zero, he
|
||
would have chosen a different strategy.
|
||
Now consider a covered call example:
|
||
Buy 100 shares TGT at $49.42
|
||
Sell 1 TGT October 50 call at 1.45
|
||
Unlimited and risk are two words that don’t sit well together with many
|
||
traders. For that reason, traders often prefer to sell calls as part of a spread.
|
||
But since spreads are strategies that involve multiple components, they have
|
||
different risk characteristics from an outright option. Perhaps the most
|
||
commonly used call-selling spread strategy is the covered call (sometimes
|
||
called a covered write or a buy-write ). While selling a call naked is a way
|
||
to take advantage of a “not bullish” forecast, the covered call achieves a
|
||
different set of objectives.
|
||
After studying Target Corporation, another trader, Isabel, has a neutral to
|
||
slightly bullish forecast. With Target at $49.42, she believes the stock will
|
||
be range-bound between $47 and $51.50 over the next two months, ending
|
||
with October expiration. Isabel buys 100 shares of Target at $49.42 and
|
||
sells 1 TGT October 50 call at 1.45. The implications for the covered-call
|
||
strategy are twofold: Isabel must be content to own the stock at current
|
||
levels, and—since she sold the right to buy the stock at $50, that is, a 50
|
||
call, to another party—she must be willing to sell the stock if the price rises
|
||
to or through $50 per share. Exhibit 1.4 shows how this covered call
|
||
performs if it is held until the call expires.
|
||
EXHIBIT 1.4 Target covered call.
|
||
The solid kinked line represents the covered call position, and the thin,
|
||
straight dotted line represents owning the stock outright. At the expiration
|
||
of the call option, if Target is trading below $50 per share—the strike price
|
||
—the call expires and Isabel is left with a long position of 100 shares plus
|
||
$1.45 per share of expired-option premium. Below the strike, the buy-write
|
||
always outperforms simply owning the stock by the amount of the
|
||
premium. The call premium provides limited downside protection; the stock
|
||
Isabel owns can decline $1.45 in value to $47.97 before the trade is a loser.
|
||
In the unlikely event the stock collapses and becomes worthless, this
|
||
limited downside protection is not so comforting. Ultimately, Isabel has
|
||
$47.97 per share at risk.
|
||
The trade-off comes if Target is above $50 at expiration. Here, assignment
|
||
will likely occur, in which case the stock will be sold. The call can be
|
||
assigned before expiration, too, causing the stock to be called away early.
|
||
Because the covered call involves this obligation to sell the sock at the
|
||
strike price, upside potential is limited. In this case, Isabel’s profit potential
|
||
is $2.03. The stock can rise from $49.42 to $50—a $0.58 profit—plus $1.45
|
||
of option premium.
|
||
Isabel does not want the stock to decline too much. Below $47.97, the
|
||
trade is a loser. If the stock rises too much, the stock is sold prematurely and
|
||
upside opportunity is lost. Limited reward and unlimited risk. (Technically,
|
||
the risk is not unlimited—the stock can only go to zero. But if the stock
|
||
drops from $49.42 to zero in a short time, the risk will certainly feel
|
||
unlimited.) The covered call strategy is for a neutral to moderately bullish
|
||
outlook.
|
||
Sell Put
|
||
Selling a put has many similarities to the covered call strategy. We’ll
|
||
discuss the two positions and highlight the likenesses. Chapter 6 will detail
|
||
the nuts and bolts of why these similarities exist.
|
||
Consider an example of selling a put:
|
||
Sell 1 BA January 65 put at 1.20
|
||
In this example, trader Sam is neutral to moderately bullish on Boeing (BA)
|
||
between now and January expiration. He is not bullish enough to buy BA at
|
||
the current market price of $69.77 per share. But if the shares dropped
|
||
below $65, he’d gladly scoop some up. Sam sells 1 BA January 65 put at
|
||
1.20. The at-expiration diagram in Exhibit 1.5 shows the P&(L) of this trade
|
||
if it is held until expiration.
|
||
EXHIBIT 1.5 Boeing short put.
|
||
At the expiration of this option, if Boeing is above $65, the put expires
|
||
and Sam retains the premium of $1.20. The obligation to buy stock expires
|
||
with the option. Below the strike, put owners will be inclined to exercise
|
||
their option to sell the stock at $65. Therefore, those short the put, as Sam is
|
||
in this example, can expect assignment. The break-even price for the
|
||
position is $63.80. That is the strike price minus the option premium. If
|
||
assigned, this is the effective purchase price of the stock. The obligation to
|
||
buy at $65 is fulfilled, but the $1.20 premium collected makes the purchase
|
||
effectively $63.80. Here, again, there is limited profit opportunity ($1.20 if
|
||
the stock is above the strike price) and seemingly unlimited risk (the risk of
|
||
potential stock ownership at $63.80) if Boeing is below the strike price.
|
||
Why would a trader short a put and willingly assume this substantial risk
|
||
with comparatively limited reward? There are a number of motivations that
|
||
may warrant the short put strategy. In this example, Sam had the twin goals
|
||
of profiting from a neutral to moderately bullish outlook on Boeing and
|
||
buying it if it traded below $65. The short put helps him achieve both
|
||
objectives.
|
||
Much like the covered call, if the stock is above the strike at expiration,
|
||
this trader reaches his maximum profit potential—in this case 1.20. And if
|
||
the price of Boeing is below the strike at expiration, Sam has ownership of
|
||
the stock from assignment. Here, a strike price that is lower than the current
|
||
stock level is used. The stock needs to decline in order for Sam to get
|
||
assigned and become long the stock. With this strategy, he was able to
|
||
establish a target price at which he would buy the stock. Why not use a limit
|
||
order? If the put is assigned, the effective purchase price is $63.80 even if
|
||
the stock price is above this price. If the put is not assigned, the premium is
|
||
kept.
|
||
A consideration every trader must make before entering the short put
|
||
position is how the purchase of the stock will be financed in the event the
|
||
put is assigned. Traders hoping to acquire the stock will often hold enough
|
||
cash in their trading account to secure the purchase of the stock. This is
|
||
called a cash-secured put . In this example, Sam would hold $6,380 in his
|
||
account in addition to the $120 of option premium received. This affords
|
||
him enough free capital to fund the $6,500 purchase of stock the short put
|
||
dictates. More speculative traders may be willing to buy the stock on
|
||
margin, in which case the trader will likely need around 50 percent of the
|
||
stock’s value.
|
||
Some traders sell puts without the intent of ever owning the stock. They
|
||
hope to profit from a low-volatility environment. Just as the short call is a
|
||
not-bullish stance on the underlying, the short put is a not-bearish play. As
|
||
long as the underlying is above the strike price at expiration, the option
|
||
premium is all profit. The trader must actively manage the position for fear
|
||
of being assigned. Buying the put back to close the position eliminates the
|
||
risk of assignment.
|
||
Buy Put
|
||
Buying a put gives the holder the right to sell stock at the strike price. Of
|
||
course, puts can be a part of a host of different spreads, but this chapter
|
||
discusses the two most basic and common put-buying strategies: the long
|
||
put and the protective put. The long put is a way to speculate on a bearish
|
||
move in the underlying security, and the protective put is a way to protect a
|
||
long position in the underlying security.
|
||
Consider a long put example:
|
||
Buy 1 SPY May 139 put at 2.30
|
||
In this example, the Spiders have had a good run up to $140.35. Trader
|
||
Isabel is looking for a 10 percent correction in SPY between now and the
|
||
end of May, about three months away. She buys 1 SPY May 139 put at 2.30.
|
||
This put gives her the right to sell 100 shares of SPY at $139 per share.
|
||
Exhibit 1.6 shows Isabel’s P&(L) if the put is held until expiration.
|
||
EXHIBIT 1.6 SPY long put.
|
||
If SPY is above the strike price of 139 at expiration, the put will expire
|
||
and the entire premium of 2.30 will be lost. If SPY is below the strike price
|
||
at expiration, the put will have value. It can be exercised, creating a short
|
||
position in the Spiders at an effective price of $136.70 per share. This price
|
||
is found by subtracting the premium paid, 2.30, from the strike price, 139.
|
||
This is the point at which the position breaks even. If SPY is below $136.70
|
||
at expiration, Isabel has a profit. Profits will increase on a tick-for-tick
|
||
basis, with downward movements in SPY down to zero. The long put has
|
||
limited risk and substantial reward potential.
|
||
An alternative for Isabel is to short the ETF at the current price of
|
||
$140.35. But a short position in the underlying may not be as attractive to
|
||
her as a long put. The margin requirements for short stock are significantly
|
||
higher than for a long put. Put buyers must post only the premium of the put
|
||
—that is the most that can be lost, after all.
|
||
The margin requirement for short stock reflects unlimited loss potential.
|
||
Margin requirements aside, risk is a very real consideration for a trader
|
||
deciding between shorting stock and buying a put. If the trader expects high
|
||
volatility, he or she may be more inclined to limit upside risk while
|
||
leveraging downside profit potential by buying a put. In general, traders buy
|
||
options when they expect volatility to increase and sell them when they
|
||
expect volatility to decrease. This will be a common theme throughout this
|
||
book.
|
||
Consider a protective put example:
|
||
This is an example of a situation in which volatility is expected to
|
||
increase.
|
||
Own 100 shares SPY at 140.35
|
||
Buy 1 SPY May139 put at 2.30
|
||
Although Isabel bought a put because she was bearish on the Spiders, a
|
||
different trader, Kathleen, may buy a put for a different reason—she’s
|
||
bullish but concerned about increasing volatility. In this example, Kathleen
|
||
has owned 100 shares of Spiders for some time. SPY is currently at
|
||
$140.35. She is bullish on the market but has concerns about volatility over
|
||
the next two or three months. She wants to protect her investment. Kathleen
|
||
buys 1 SPY May 139 put at 2.30. (If Kathleen bought the shares of SPY and
|
||
the put at the same time, as a spread, the position would be called a married
|
||
put.)
|
||
Kathleen is buying the right to sell the shares she owns at $139.
|
||
Effectively, it is an insurance policy on this asset. Exhibit 1.7 shows the risk
|
||
profile of this new position.
|
||
EXHIBIT 1.7 SPY protective put.
|
||
The solid kinked line is the protective put (put and stock), and the thin
|
||
dotted line is the outright position in SPY alone, without the put. The most
|
||
Kathleen stands to lose with the protective put is $3.65 per share. SPY can
|
||
decline from $140.35 to $139, creating a loss of $1.35, plus the $2.30
|
||
premium spent on the put. If the stock does not fall and the insuring put
|
||
hence does not come into play, the cost of the put must be recouped to
|
||
justify its expense. The break-even point is $142.65.
|
||
This position implies that Kathleen is still bullish on the Spiders. When
|
||
traders believe a stock or ETF is going to decline, they sell the shares.
|
||
Instead, Kathleen sacrifices 1.6 percent of her investment up front by
|
||
purchasing the put for $2.30. She defers the sale of SPY until the period of
|
||
perceived risk ends. Her motivation is not to sell the ETF; it is to hedge
|
||
volatility.
|
||
Once the anticipated volatility is no longer a concern, Kathleen has a
|
||
choice to make. She can let the option run its course, holding it to
|
||
expiration, at which point it will either expire or be exercised; or she can
|
||
sell the option before expiration. If the option is out-of-the-money, it may
|
||
have residual time value prior to expiration that can be recouped. If it is in-
|
||
the-money, it will have intrinsic value and maybe time value as well. In this
|
||
situation, Kathleen can look at this spread as two trades—one that has
|
||
declined in price, the SPY shares, and one that has risen in price, the put.
|
||
Losses on the ETF shares are to some degree offset by gains on the put.
|
||
Measuring Incremental Changes in
|
||
Factors Affecting Option Prices
|
||
At-expiration diagrams are very helpful in learning how a particular option
|
||
strategy works. They show what the option’s price will ultimately be at
|
||
various prices of the underlying. There is, however, a caveat when using at-
|
||
expiration diagrams. According to the Options Industry Council, most
|
||
options are closed before they reach expiration. Traders not planning to
|
||
hold an option until it expires need to have a way to develop reasonable
|
||
expectations as to what the option’s price will be given changes that can
|
||
occur in factors affecting the option’s price. The tool option traders use to
|
||
aid them in this process is option greeks.
|
||
CHAPTER 2
|
||
Greek Philosophy
|
||
My wife, Kathleen, is not an options trader. Au contraire. However, she,
|
||
like just about everyone, uses them from time to time—though without
|
||
really thinking about it. She was on eBay the other day bidding on a pair of
|
||
shoes. The bid was $45 with three days left to go. She was concerned about
|
||
the price rising too much and missing the chance to buy them at what she
|
||
thought was a good price. She noticed, though, that someone else was
|
||
selling the same shoes with a buy-it-now price of $49—a good-enough
|
||
price in her opinion. Kathleen was effectively afforded a call option. She
|
||
had the opportunity to buy the shoes at (the strike price of) $49, a right she
|
||
could exercise until the offer expired.
|
||
The biggest difference between the option in the eBay scenario and the
|
||
sort of options discussed in this book is transferability. Actual options are
|
||
tradable—they can be bought and sold. And it is the contract itself that has
|
||
value—there is one more iteration of pricing.
|
||
For example, imagine the $49 opportunity was a coupon or certificate that
|
||
guaranteed the price of $49, which could be passed along from one person
|
||
to another. And there was the chance that the $49-price guarantee could
|
||
represent a discount on the price paid for the shoes—maybe a big discount
|
||
—should the price of the shoes rise in the eBay auction. The certificate
|
||
guaranteeing the $49 would have value. Anyone planning to buy the shoes
|
||
would want the safety of knowing they were guaranteed not to pay more
|
||
than $49 for the shoes. In fact, some people would even consider paying to
|
||
buy the certificate itself if they thought the price of the shoes might rise
|
||
significantly.
|
||
Price vs. Value: How Traders Use
|
||
Option-Pricing Models
|
||
Like in the common-life example just discussed, the right to buy or sell an
|
||
underlying security—that is, an option—can have value, too. The specific
|
||
value of an option is determined by supply and demand. There are several
|
||
variables in an option contract, however, that can influence a trader’s
|
||
willingness to demand (desire to buy) or supply (desire to sell) an option at
|
||
a given price. For example, a trader would rather own—that is, there would
|
||
be higher demand for—an option that has more time until expiration than a
|
||
shorter-dated option, all else held constant. And a trader would rather own a
|
||
call with a lower strike than a higher strike, all else kept constant, because it
|
||
would give the right to buy at a lower price.
|
||
Several elements contribute to the value of an option. It took academics
|
||
many years to figure out exactly what those elements are. Fischer Black and
|
||
Myron Scholes together pioneered research in this area at the University of
|
||
Chicago. Ultimately, their work led to a Nobel Prize for Myron Scholes.
|
||
Fischer Black died before he could be honored.
|
||
In 1973, Black and Scholes published a paper called “The Pricing of
|
||
Options and Corporate Liabilities” in the Journal of Political Economy ,
|
||
that introduced the Black-Scholes option-pricing model to the world. The
|
||
Black-Scholes model values European call options on non-dividend-paying
|
||
stocks. Here, for the first time, was a widely accepted model illustrating
|
||
what goes into the pricing of an option. Option prices were no longer wild
|
||
guesswork. They could now be rationalized. Soon, additional models and
|
||
alterations to the Black-Scholes model were developed for options on
|
||
indexes, dividend-paying stocks, bonds, commodities, and other optionable
|
||
instruments. All the option-pricing models commonly in use today have
|
||
slightly different means but achieve the same end: the option’s theoretical
|
||
value. For American-exercise equity options, six inputs are entered into any
|
||
option-pricing model to generate a theoretical value: stock price, strike
|
||
price, time until expiration, interest rate, dividends, and volatility.
|
||
Theoretical value—what a concept! A trader plugs six numbers into a
|
||
pricing model, and it tells him what the option is worth, right? Well, in
|
||
practical terms, that’s not exactly how it works. An option is worth what the
|
||
market bears. Economists call this price discovery. The price of an option is
|
||
determined by the forces of supply and demand working in a free and open
|
||
market. Herein lies an important concept for option traders: the difference
|
||
between price and value.
|
||
Price can be observed rather easily from any source that offers option
|
||
quotes (web sites, your broker, quote vendors, and so on). Value is
|
||
calculated by a pricing model. But, in practice, the theoretical value is really
|
||
not an output at all. It is already known: the market determines it. The trader
|
||
rectifies price and value by setting the theoretical value to fall between the
|
||
bid and the offer of the option by adjusting the inputs to the model.
|
||
Professional traders often refer to the theoretical value as the fair value of
|
||
the option.
|
||
At this point, please note the absence of the mathematical formula for the
|
||
Black-Scholes model (or any other pricing model, for that matter).
|
||
Although the foundation of trading option greeks is mathematical, this book
|
||
will keep the math to a minimum—which is still quite a bit. The focus of
|
||
this book is on practical applications, not academic theory. It’s about
|
||
learning to drive the car, not mastering its engineering.
|
||
The trader has an equation with six inputs equaling one known output.
|
||
What good is this equation? An option-pricing model helps a trader
|
||
understand how market forces affect the value of an option. Five of the six
|
||
inputs are dynamic; the only constant is the strike price of the option in
|
||
question. If the price of the option changes, it’s because one or more of the
|
||
five variable inputs has changed. These variables are independent of each
|
||
other, but they can change in harmony, having either a cumulative or net
|
||
effect on the option’s value. An option trader needs to be concerned with the
|
||
relationship of these variables (price, time, volatility, interest). This
|
||
multidimensional view of asset pricing is unique to option traders.
|
||
Delta
|
||
The five figures commonly used by option traders are represented by Greek
|
||
letters: delta, gamma, theta, vega, rho. The figures are referred to as option
|
||
greeks. Vega, of course, is not an actual letter of the greek alphabet, but in
|
||
the options vernacular, it is considered one of the greeks.
|
||
The greeks are a derivation of an option-pricing model, and each Greek
|
||
letter represents a specific sensitivity to influences on the option’s value. To
|
||
understand concepts represented by these five figures, we’ll start with delta,
|
||
which is defined in four ways:
|
||
1. The rate of change of an option value relative to a change in the
|
||
underlying stock price.
|
||
2. The derivative of the graph of an option value in relation to the stock
|
||
price.
|
||
3. The equivalent of underlying shares represented by an option
|
||
position.
|
||
4. The estimate of the likelihood of an option expiring in-the-money. 1
|
||
Definition 1 : Delta (Δ) is the rate of change of an option’s value relative
|
||
to a change in the price of the underlying security. A trader who is bullish
|
||
on a particular stock may choose to buy a call instead of buying the
|
||
underlying security. If the price of the stock rises by $1, the trader would
|
||
expect to profit on the call—but by how much? To answer that question, the
|
||
trader must consider the delta of the option.
|
||
Delta is stated as a percentage. If an option has a 50 delta, its price will
|
||
change by 50 percent of the change of the underlying stock price. Delta is
|
||
generally written as either a whole number, without the percent sign, or as a
|
||
decimal. So if an option has a 50 percent delta, this will be indicated as
|
||
0.50, or 50. For the most part, we’ll use the former convention in our
|
||
discussion.
|
||
Call values increase when the underlying stock price increases and vice
|
||
versa. Because calls have this positive correlation with the underlying, they
|
||
have positive deltas. Here is a simplified example of the effect of delta on
|
||
an option:
|
||
Consider a $60 stock with a call option that has a 0.50 delta and is trading
|
||
for 3.00. Considering only the delta, if the stock price increases by $1, the
|
||
theoretical value of the call will rise by 0.50. That’s 50 percent of the stock
|
||
price change. The new call value will be 3.50. If the stock price decreases
|
||
by $1, the 0.50 delta will cause the call to decrease in value by 0.50, from
|
||
3.00 to 2.50.
|
||
Puts have a negative correlation to the underlying. That is, put values
|
||
decrease when the stock price rises and vice versa. Puts, therefore, have
|
||
negative deltas. Here is a simplified example of the delta effect on a −0.40-
|
||
delta put:
|
||
As the stock rises from $60 to $61, the delta of −0.40 causes the put value
|
||
to go from $2.25 to $1.85. The put decreases by 40 percent of the stock
|
||
price increase. If the stock price instead declined by $1, the put value would
|
||
increase by $0.40, to $2.65.
|
||
Unfortunately, real life is a bit more complicated than the simplified
|
||
examples of delta used here. In reality, the value of both the call and the put
|
||
will likely be higher with the stock at $61 than was shown in these
|
||
examples. We’ll expand on this concept later when we tackle the topic of
|
||
gamma.
|
||
Definition 2 : Delta can also be described another way. Exhibit 2.1 shows
|
||
the value of a call option with three months to expiration at a variable stock
|
||
price. As the stock price rises, the call is worth more; as the stock price
|
||
declines, the call value moves toward zero. Mathematically, for any given
|
||
point on the graph, the derivative will show the rate of change of the option
|
||
price. The delta is the first derivative of the graph of the option price
|
||
relative to the stock price .
|
||
EXHIBIT 2.1 Call value compared with stock price.
|
||
Definition 3 : In terms of absolute value (meaning that plus and minus
|
||
signs are ignored), the delta of an option is between 1.00 and 0. Its price can
|
||
change in tandem with the stock, as with a 1.00 delta; or it cannot change at
|
||
all as the stock moves, as with a 0 delta; or anything in between. By
|
||
definition, stock has a 1.00 delta—it is the underlying security. A $1 rise in
|
||
the stock yields a $100 profit on a round lot of 100 shares. A call with a
|
||
0.60 delta rises by $0.60 with a $1 increase in the stock. The owner of a call
|
||
representing rights on 100 shares earns $60 for a $1 increase in the
|
||
underlying. It’s as if the call owner in this example is long 60 shares of the
|
||
underlying stock. Delta is the option’s equivalent of a position in the
|
||
underlying shares .
|
||
A trader who buys five 0.43-delta calls has a position that is effectively
|
||
long 215 shares—that’s 5 contracts × 0.43 deltas × 100 shares. In option
|
||
lingo, the trader is long 215 deltas. Likewise, if the trader were short five
|
||
0.43-delta calls, the trader would be short 215 deltas.
|
||
The same principles apply to puts. Being long 10 0.59-delta puts makes
|
||
the trader short a total of 590 deltas, a position that profits or loses like
|
||
being short 590 shares of the underlying stock. Conversely, if the trader
|
||
were short 10 0.59-delta puts, the trader would theoretically make $590 if
|
||
the stock were to rise $1 and lose $590 if the stock fell by $1—just like
|
||
being long 590 shares.
|
||
Definition 4 : The final definition of delta is considered the trader’s
|
||
definition. It’s mathematically imprecise but is used nonetheless as a
|
||
general rule of thumb by option traders. A trader would say the delta is a
|
||
statistical approximation of the likelihood of the option expiring in-the-
|
||
money . An option with a 0.75 delta would have a 75 percent chance of
|
||
being in-the-money at expiration under this definition. An option with a
|
||
0.20 delta would be thought of having a 20 percent chance of expiring in-
|
||
the-money.
|
||
Dynamic Inputs
|
||
Option deltas are not constants. They are calculated from the dynamic
|
||
inputs of the pricing model—stock price, time to expiration, volatility, and
|
||
so on. When these variables change, the changes affect the delta. These
|
||
changes can be mathematically quantified—they are systematic.
|
||
Understanding these patterns and other quirks as to how delta behaves can
|
||
help traders use this tool more effectively. Let’s discuss a few observations
|
||
about the characteristics of delta.
|
||
First, call and put deltas are closely related. Exhibit 2.2 is a partial option
|
||
chain of 70-day calls and puts in Rambus Incorporated (RMBS). The stock
|
||
was trading at $21.30 when this table was created. In Exhibit 2.2 , the 20
|
||
calls have a 0.66 delta.
|
||
EXHIBIT 2.2 RMBS Option chain with deltas.
|
||
Notice the deltas of the put-call pairs in this exhibit. As a general rule, the
|
||
absolute value of the call delta plus the absolute value of the put delta add
|
||
up to close to 1.00. The reason for this has to do with a mathematical
|
||
relationship called put-call parity, which is briefly discussed later in this
|
||
chapter and described in detail in Chapter 6. But with equity options, the
|
||
put-call pair doesn’t always add up to exactly 1.00.
|
||
Sometimes the difference is simply due to rounding. But sometimes there
|
||
are other reasons. For example, the 30-strike calls and puts in Exhibit 2.2
|
||
have deltas of 0.14 and −0.89, respectively. The absolute values of the
|
||
deltas add up to 1.03. Because of the possibility of early exercise of
|
||
American options, the put delta is a bit higher than the call delta would
|
||
imply. When puts have a greater chance of early exercise, they begin to act
|
||
more like short stock and consequently will have a greater delta. Often,
|
||
dividend-paying stocks will have higher deltas on some in-the-money calls
|
||
than the put in the pair would imply. As the ex-dividend date—the date the
|
||
stock begins trading without the dividend—approaches, an in-the-money
|
||
call can become more apt to be exercised, because traders will want to own
|
||
stock to capture the dividend. Here, the call begins to act more like long
|
||
stock, leading to a higher delta.
|
||
Moneyness and Delta
|
||
The next observation is the effect of moneyness on the option’s delta.
|
||
Moneyness describes the degree to which the option is in- or out-of-the-
|
||
money. As a general rule, options that are in-the-money (ITM) have deltas
|
||
greater than 0.50. Options that are out-of-the-money (OTM) have deltas
|
||
less than 0.50. Finally, options that are at-the-money (ATM) have deltas that
|
||
are about 0.50. The more in-the-money the option is, the closer to 1.00 the
|
||
delta is. The more out-of-the-money, the closer the delta is to 0.
|
||
But ATM options are usually not exactly 0.50. For ATMs, both the call
|
||
and the put deltas are generally systematically a value other than 0.50.
|
||
Typically, the call has a higher delta than 0.50 and the put has a lower
|
||
absolute value than 0.50. Incidentally, the call’s theoretical value is
|
||
generally greater than the put’s when the options are right at-the-money as
|
||
well. One reason for this disparity between exactly at-the-money calls and
|
||
puts is the interest rate. The more time until expiration, the more effect the
|
||
interest rate will have, and, therefore, the higher the call’s theoretical and
|
||
delta will be relative to the put.
|
||
Effect of Time on Delta
|
||
In a close contest, the last few minutes of a football game are often the most
|
||
exciting—not because the players run faster or knock heads harder but
|
||
because one strategic element of the game becomes more and more
|
||
important: time. The team that’s in the lead wants the game clock to run
|
||
down with no interruption to solidify its position. The team that’s losing
|
||
uses its precious time-outs strategically. The more playing time left, the less
|
||
certain defeat is for the losing team.
|
||
Although mathematically imprecise, the trader’s definition can help us
|
||
gain insight into how time affects option deltas. The more time left until an
|
||
option’s expiration, the less certain it is whether the option will be ITM or
|
||
OTM at expiration. The deltas of both the ITM and the OTM options reflect
|
||
that uncertainty. The more time left in the life of the option, the closer the
|
||
deltas tend to gravitate to 0.50. A 0.50 delta represents the greatest level of
|
||
uncertainty—a coin toss. Exhibit 2.3 shows the deltas of a hypothetical
|
||
equity call with a strike price of 50 at various stock prices with different
|
||
times until expiration. All other parameters are held constant.
|
||
EXHIBIT 2.3 Estimated delta of 50-strike call—impact of time.
|
||
|
||
As shown in Exhibit 2.3 , the more time until expiration, the closer ITMs
|
||
and OTMs move to 0.50. At expiration, of course, the option is either a 100
|
||
delta or a 0 delta; it’s either stock or not.
|
||
Effect of Volatility on Delta
|
||
The level of volatility affects option deltas as well. We’ll discuss volatility
|
||
in more detail in future chapters, but it’s important to address it here as it
|
||
relates to the concept of delta. Exhibit 2.4 shows how changing the
|
||
volatility percentage (explained further in Chapter 3), as opposed to the
|
||
time to expiration, affects option deltas. In this table, the delta of a call with
|
||
91 days until expiration is studied.
|
||
EXHIBIT 2.4 Estimated delta of 50-strike call—impact of volatility.
|
||
Notice the effect that volatility has on the deltas of this option with the
|
||
underlying stock at various prices. In this table, at a low volatility with the
|
||
call deep in- or out-of-the-money, the delta is very large or very small,
|
||
respectively. At 10 percent volatility with the stock at $58 a share, the delta
|
||
is 1.00. At that same volatility level with the stock at $42 a share, the delta
|
||
is 0.
|
||
But at higher volatility levels, the deltas change. With the stock at $58, a
|
||
45 percent volatility gives the 50-strike call a 0.79 delta—much smaller
|
||
than it was at the low volatility level. With the stock at $42, a 45-percent
|
||
volatility returns a 0.30 delta for the call. Generally speaking, ITM option
|
||
deltas are smaller given a higher volatility assumption, and OTM option
|
||
deltas are bigger with a higher volatility.
|
||
Effect of Stock Price on Delta
|
||
An option that is $5 in-the-money on a $20 stock will have a higher delta
|
||
than an option that is $5 in-the-money on a $200 stock. Proportionately, the
|
||
former is more in-the-money. Comparing two options that are in-the-money
|
||
by the same percentage yields similar results.
|
||
As the stock price changes because the strike price remains stable, the
|
||
option’s delta will change. This phenomenon is measured by the option’s
|
||
gamma.
|
||
Gamma
|
||
The strike price is the only constant in the pricing model. When the stock
|
||
price moves relative to this constant, the option in question becomes more
|
||
in-the-money or out-of-the-money. This means the delta changes. This
|
||
isolated change is measured by the option’s gamma, sometimes called
|
||
curvature .
|
||
Gamma (Γ) is the rate of change of an option’s delta given a change in
|
||
the price of the underlying security . Gamma is conventionally stated in
|
||
terms of deltas per dollar move. The simplified examples above under
|
||
Definition 1 of delta, used to describe the effect of delta, had one important
|
||
piece of the puzzle missing: gamma. As the stock price moved higher in
|
||
those examples, the delta would not remain constant. It would change due
|
||
to the effect of gamma. The following example shows how the delta would
|
||
change given a 0.04 gamma attributed to the call option.
|
||
The call in this example starts as a 0.50-delta option. When the stock
|
||
price increases by $1, the delta increases by the amount of the gamma. In
|
||
this example, delta increases from 0.50 to 0.54, adding 0.04 deltas. As the
|
||
stock price continues to rise, the delta continues to move higher. At $62, the
|
||
call’s delta is 0.58.
|
||
This increase in delta will affect the value of the call. When the stock
|
||
price first begins to rise from $60, the option value is increasing at a rate of
|
||
50 percent—the call’s delta at that stock price. But by the time the stock is
|
||
at $61, the option value is increasing at a rate of 54 percent of the stock
|
||
price. To estimate the theoretical value of the call at $61, we must first
|
||
estimate the average change in the delta between $60 and $61. The average
|
||
delta between $60 and $61 is roughly 0.52. It’s difficult to calculate the
|
||
average delta exactly because gamma is not constant; this is discussed in
|
||
more detail later in the chapter. A more realistic example of call values in
|
||
relation to the stock price would be as follows:
|
||
Each $1 increase in the stock shows an increase in the call value about
|
||
equal to the average delta value between the two stock prices. If the stock
|
||
were to decline, the delta would get smaller at a decreasing rate.
|
||
As the stock price declines from $60 to $59, the option delta decreases
|
||
from 0.50 to 0.46. There is an average delta of about 0.48 between the two
|
||
stock prices. At $59 the new theoretical value of the call is 2.52. The
|
||
gamma continues to affect the option’s delta and thereby its theoretical
|
||
value as the stock continues its decline to $58 and beyond.
|
||
Puts work the same way, but because they have a negative delta, when
|
||
there is a positive stock-price movement the gamma makes the put delta
|
||
less negative, moving closer to 0. The following example clarifies this.
|
||
As the stock price rises, this put moves more and more out-of-the-money.
|
||
Its theoretical value is decreasing by the rate of the changing delta. At $60,
|
||
the delta is −0.40. As the stock rises to $61, the delta changes to −0.36. The
|
||
average delta during that move is about −0.38, which is reflected in the
|
||
change in the value of the put.
|
||
If the stock price declines and the put moves more toward being in-the-
|
||
money, the delta becomes more negative—that is, the put acts more like a
|
||
short stock position.
|
||
Here, the put value rises by the average delta value between each
|
||
incremental change in the stock price.
|
||
These examples illustrate the effect of gamma on an option without
|
||
discussing the impact on the trader’s position. When traders buy options,
|
||
they acquire positive gamma. Since gamma causes options to gain value at
|
||
a faster rate and lose value at a slower rate, (positive) gamma helps the
|
||
option buyer. A trader buying one call or put in these examples would have
|
||
+0.04 gamma. Buying 10 of these options would give the trader a +0.4
|
||
gamma.
|
||
When traders sell options, gamma works against them. When options lose
|
||
value, they move toward zero at a slower rate. When the underlying moves
|
||
adversely, gamma speeds up losses. Selling options yields a negative
|
||
gamma position. A trader selling one of the above calls or puts would have
|
||
−0.04 gamma per option.
|
||
The effect of gamma is less significant for small moves in the underlying
|
||
than it is for bigger moves. On proportionately large moves, the delta can
|
||
change quite a bit, making a big difference in the position’s P&(L). In
|
||
Exhibit 2.1 , the left side of the diagram showed the call price not
|
||
increasing at all with advances in the stock—a 0 delta. The right side
|
||
showed the option advancing in price 1-to-1 with the stock—a 1.00 delta.
|
||
Between the two extremes, the delta changes. From this diagram another
|
||
definition for gamma can be inferred: gamma is the second derivative of the
|
||
graph of the option price relative to the stock price. Put another way,
|
||
gamma is the first derivative of a graph of the delta relative to the stock
|
||
price. Exhibit 2.5 illustrates the delta of a call relative to the stock price.
|
||
EXHIBIT 2.5 Call delta compared with stock price.
|
||
Not only does the delta change, but it changes at a changing rate. Gamma
|
||
is not constant. Moneyness, time to expiration, and volatility each have an
|
||
effect on the gamma of an option.
|
||
Dynamic Gamma
|
||
When options are far in-the-money or out-of-the-money, they are either
|
||
1.00 delta or 0 delta. At the extremes, small changes in the stock price will
|
||
not cause the delta to change much. When an option is at-the-money, it’s a
|
||
different story. Its delta can change very quickly.
|
||
ITM and OTM options have a low gamma.
|
||
ATM options have a relatively high gamma.
|
||
Exhibit 2.6 is an example of how moneyness translates into gamma on
|
||
QQQ calls.
|
||
EXHIBIT 2.6 Gamma of QQQ calls with QQQ at $44.
|
||
With QQQ at $44, 92 days until expiration, and a constant volatility input
|
||
of 19 percent, the 36- and 54-strike calls are far enough in- and out-of-the-
|
||
money, respectively, that if the Qs move a small amount in either direction
|
||
from the current price of $44, the movement won’t change their deltas
|
||
much at all. The chances of their money status changing between now and
|
||
expiration would not be significantly different statistically given a small
|
||
stock price change. They have the smallest gammas in the table.
|
||
The highest gammas shown here are around the ATM strike prices. (Note
|
||
that because of factors not yet discussed, the strike that is exactly at-the-
|
||
money may not have the highest gamma. The highest gamma is likely to
|
||
occur at a slightly higher strike price.) Exhibit 2.7 shows a graph of the
|
||
corresponding numbers in Exhibit 2.6 .
|
||
EXHIBIT 2.7 Option gamma.
|
||
A decrease in the time to expiration solidifies the likelihood of ITMs or
|
||
OTMs remaining as such. But an ATM option’s moneyness at expiration
|
||
remains to the very end uncertain. As expiration draws nearer, the gamma
|
||
decreases for ITMs and OTMs and increases for the ATM strikes. Exhibit
|
||
2.8 shows the same 92-day QQQ calls plotted against 7-day QQQ calls.
|
||
EXHIBIT 2.8 Gamma as time passes.
|
||
|
||
At seven days until expiration, there is less time for price action in the
|
||
stock to change the expected moneyness at expiration of ITMs or OTMs.
|
||
ATM options, however, continue to be in play. Here, the ATM gamma is
|
||
approaching 0.35. But the strikes below 41 and above 48 have 0 gamma.
|
||
Similarly-priced securities that tend to experience bigger price swings
|
||
may have strikes $3 away-from-the-money with seven-day gammas greater
|
||
than zero. The volatility of the underlying will affect gamma, too. Exhibit
|
||
2.9 shows the same 19 percent volatility QQQ calls in contrast with a graph
|
||
of the gamma if the volatility is doubled.
|
||
EXHIBIT 2.9 Gamma as volatility changes.
|
||
Raising the volatility assumption flattens the curve, causing ITM and
|
||
OTM to have higher gamma while lowering the gamma for ATMs.
|
||
Short-term ATM options with low volatility have the highest gamma.
|
||
Lower gamma is found in ATMs when volatility is higher and it is lower for
|
||
ITMs and OTMs and in longer-dated options.
|
||
Theta
|
||
Option prices can be broken down into two parts: intrinsic value and time
|
||
value. Intrinsic value is easily measurable. It is simply the ITM part of the
|
||
premium. Time value, or extrinsic value, is what’s left over—the premium
|
||
paid over parity for the option. All else held constant, the more time left in
|
||
the life of the option, the more valuable it is—there is more time for the
|
||
stock to move. And as the useful life of an option decreases, so does its time
|
||
value.
|
||
The decline in the value of an option because of the passage of time is
|
||
called time decay, or erosion. Incremental measurements of time decay are
|
||
represented by the Greek letter theta (θ). Theta is the rate of change in an
|
||
option’s price given a unit change in the time to expiration . What exactly is
|
||
the unit involved here? That depends.
|
||
Some providers of option greeks will display thetas that represent one
|
||
day’s worth of time decay. Some will show thetas representing seven days
|
||
of decay. In the case of a one-day theta, the figure may be based on a seven-
|
||
day week or on a week counting only trading days. The most common and,
|
||
arguably, most useful display of this figure is the one-day theta based on the
|
||
seven-day week. There are, after all, seven days in a week, each day of
|
||
which can see an occurrence with the potential to cause a revaluation in the
|
||
stock price (that is, news can come out on Saturday or Sunday). The one-
|
||
day theta based on a seven-day week will be used throughout this book.
|
||
Taking the Day Out
|
||
When the number of days to expiration used in the pricing model declines
|
||
from, say, 32 days to 31 days, the price of the option decreases by the
|
||
amount of the theta, all else held constant. But when is the day “taken out”?
|
||
It is intuitive to think that after the market closes, the model is changed to
|
||
reflect the passing of one day’s time. But, in fact, this change is logically
|
||
anticipated and may be priced in early.
|
||
In the earlier part of the week, option prices can often be observed getting
|
||
cheaper relative to the stock price sometime in the middle of the day. This is
|
||
because traders will commonly take the day out of their model during
|
||
trading hours after the underlying stabilizes following the morning
|
||
business. On Fridays and sometimes Thursdays, traders will take all or part
|
||
of the weekend out. Commonly, by Friday afternoon, traders will be using
|
||
Monday’s days to value their options.
|
||
When option prices are seen getting cheaper on, say, a Friday, how can
|
||
one tell whether this is the effect of the market taking the weekend out or a
|
||
change in some other input, such as volatility? To some degree, it doesn’t
|
||
matter. Remember, the model is used to reflect what the market is doing,
|
||
not the other way around. In many cases, it’s logical to presume that small
|
||
devaluations in option prices intraday can be attributed to the routine of the
|
||
market taking the day out.
|
||
Friend or Foe?
|
||
Theta can be a good thing or a bad thing, depending on the position. Theta
|
||
hurts long option positions; whereas it helps short option positions. Take an
|
||
80-strike call with a theoretical value of 3.16 on a stock at $82 a share. The
|
||
32-day 80 call has a theta of 0.03. If a trader owned one of these calls, the
|
||
trader’s position would theoretically lose 0.03, or $0.03, as the time until
|
||
expiration change from 32 to 31 days. This trader has a negative theta
|
||
position. A trader short one of these calls would have an overnight
|
||
theoretical profit of $0.03 attributed to theta. This trader would have a
|
||
positive theta.
|
||
Theta affects put traders as well. Using all the same modeling inputs, the
|
||
32-day 80-strike put would have a theta of 0.02. A put holder would
|
||
theoretically lose $0.02 a day, and a put writer would theoretically make
|
||
$0.02. Long options carry with them negative theta; short options carry
|
||
positive theta.
|
||
A higher theta for the call than for the put of the same strike price is
|
||
common when an interest rate greater than zero is used in the pricing
|
||
model. As will be discussed in greater detail in the section on rho, interest
|
||
causes the time value of the call to be higher than that of the corresponding
|
||
put. At expiration, there is no time value left in either option. Because the
|
||
call begins with more time value, its premium must decline at a faster rate
|
||
than that of the put. Most modeling software will attribute the disparate
|
||
rates of decline in value all to theta, whereas some modeling interfaces will
|
||
make clear the distinction between the effect of time decay and the effect of
|
||
interest on the put-call pair.
|
||
The Effect of Moneyness and Stock Price
|
||
on Theta
|
||
Theta is not a constant. As variables influencing option values change, theta
|
||
can change, too. One such variable is the option’s moneyness. Exhibit 2.10
|
||
shows theoretical values (theos), time values, and thetas for 3-month
|
||
options on Adobe (ADBE). In this example, Adobe is trading at $31.30 a
|
||
share with three months until expiration. The more ITM a call or a put gets,
|
||
the higher its theoretical value. But when studying an option’s time decay,
|
||
one needs to be concerned only with the option’s time value, because
|
||
intrinsic value is not subject to time decay.
|
||
EXHIBIT 2.10 Adobe theos and thetas (Adobe at $31.30).
|
||
The ATM options shown here have higher time value than ITM or OTM
|
||
options. Hence, they have more time premium to lose in the same three-
|
||
month period. ATM options have the highest rate of decay, which is
|
||
reflected in higher thetas. As the stock price changes, the theta value will
|
||
change to reflect its change in moneyness.
|
||
If this were a higher-priced stock, say, 10 times the stock price used in
|
||
this example, with all other inputs held constant, the option values, and
|
||
therefore the thetas, would be higher. If this were a stock trading at $313,
|
||
the 325-strike call would have a theoretical value of 16.39 and a one-day
|
||
theta of 0.189, given inputs used otherwise identical to those in the Adobe
|
||
example.
|
||
The Effects of Volatility and Time on
|
||
Theta
|
||
Stock price is not the only factor that affects theta values. Volatility and
|
||
time to expiration come into play here as well. The volatility input to the
|
||
pricing model has a direct relationship to option values. The higher the
|
||
volatility, the higher the value of the option. Higher-valued options decay at
|
||
a faster rate than lower-valued options—they have to; their time values will
|
||
both be zero at expiration. All else held constant, the higher the volatility
|
||
assumption, the higher the theta.
|
||
The days to expiration have a direct relationship to option values as well.
|
||
As the number of days to expiration decreases, the rate at which an option
|
||
decays may change, depending on the relationship of the stock price to the
|
||
strike price. ATM options tend to decay at a nonlinear rate—that is, they
|
||
lose value faster as expiration approaches—whereas the time values of ITM
|
||
and OTM options decay at a steadier rate.
|
||
Consider a hypothetical stock trading at $70 a share. Exhibit 2.11 shows
|
||
how the theoretical values of the 75-strike call and the 70-strike call decline
|
||
with the passage of time, holding all other parameters constant.
|
||
EXHIBIT 2.11 Rate of decay: ATM vs. OTM.
|
||
|
||
The OTM 75-strike call has a fairly steady rate of time decay over this
|
||
26-week period. The ATM 70-strike call, however, begins to lose its value
|
||
at an increasing rate as expiration draws nearer. The acceleration of
|
||
premium erosion continues until the option expires. Exhibit 2.12 shows the
|
||
thetas for this ATM call during the last 10 days before expiration.
|
||
EXHIBIT 2.12 Theta as expiration approaches.
|
||
Days to Exp .ATM Theta
|
||
10 0.075
|
||
9 0.079
|
||
8 0.084
|
||
7 0.089
|
||
6 0.096
|
||
5 0.106
|
||
4 0.118
|
||
3 0.137
|
||
2 0.171
|
||
1 0.443
|
||
Incidentally, in this example, when there is one day to expiration, the
|
||
theoretical value of this call is about 0.44. The final day before expiration
|
||
ultimately sees the entire time premium erode.
|
||
Vega
|
||
Over the past decade or so, computers have revolutionized option trading.
|
||
Options traded through an online broker are filled faster than you can say,
|
||
“Oops! I meant to click on puts.” Now trading is facilitated almost entirely
|
||
online by professional and retail traders alike. Market and trading
|
||
information is disseminated worldwide in subseconds, making markets all
|
||
the more efficient. And the tools now available to the common retail trader
|
||
are very powerful as well. Many online brokers and other web sites offer
|
||
high-powered tools like screeners, which allow traders to sift through
|
||
thousands of options to find those that fit certain parameters.
|
||
Using a screener to find ATM calls on same-priced stocks—say, stocks
|
||
trading at $40 a share—can yield a result worth talking about here. One $40
|
||
stock can have a 40-strike call trading at around 0.50, while a different $40
|
||
stock can have a 40 call with the same time to expiration trading at more
|
||
like 2.00. Why? The model doesn’t know the name of the company, what
|
||
industry it’s in, or what its price-to-earnings ratio is. It is a mathematical
|
||
equation with six inputs. If five of the inputs—the stock price, strike price,
|
||
time to expiration, interest rate, and dividends—are identical for two
|
||
different options but they’re trading at different prices, the difference must
|
||
be the sixth variable, which is volatility.
|
||
Implied Volatility (IV) and Vega
|
||
The volatility component of option values is called implied volatility (IV).
|
||
(For more on implied volatility and how it relates to vega, see Chapter 3.)
|
||
IV is a percentage, although in practice the percent sign is often omitted.
|
||
This is the value entered into a pricing model, in conjunction with the other
|
||
variables, that returns the option’s theoretical value. The higher the
|
||
volatility input, the higher the theoretical value, holding all other variables
|
||
constant. The IV level can change and often does—sometimes dramatically.
|
||
When IV rises or falls, option prices rise and fall in line with it. But by how
|
||
much?
|
||
The relationship between changes in IV and changes in an option’s value
|
||
is measured by the option’s vega. Vega is the rate of change of an option’s
|
||
theoretical value relative to a change in implied volatility . Specifically, if
|
||
the IV rises or declines by one percentage point, the theoretical value of the
|
||
option rises or declines by the amount of the option’s vega, respectively.
|
||
For example, if a call with a theoretical value of 1.82 has a vega of 0.06 and
|
||
IV rises one percentage point from, say, 17 percent to 18 percent, the new
|
||
theoretical value of the call will be 1.88—it would rise by 0.06, the amount
|
||
of the vega. If, conversely, the IV declines 1 percentage point, from 17
|
||
percent to 16 percent, the call value will drop to 1.76—that is, it would
|
||
decline by the vega.
|
||
A put with the same expiration month and the same strike on the same
|
||
underlying will have the same vega value as its corresponding call. In this
|
||
example, raising or lowering IV by one percentage point would cause the
|
||
corresponding put value to rise or decline by $0.06, just like the call.
|
||
An increase in IV and the consequent increase in option value helps the
|
||
P&(L) of long option positions and hurts short option positions. Buying a
|
||
call or a put establishes a long vega position. For short options, the opposite
|
||
is true. Rising IV adversely affects P&(L), whereas falling IV helps.
|
||
Shorting a call or put establishes a short vega position.
|
||
The Effect of Moneyness on Vega
|
||
Like the other greeks, vega is a snapshot that is a function of multiple facets
|
||
of determinants influencing option value. The stock price’s relationship to
|
||
the strike price is a major determining factor of an option’s vega. IV affects
|
||
only the time value portion of an option. Because ATM options have the
|
||
greatest amount of time value, they will naturally have higher vegas. ITM
|
||
and OTM options have lower vega values than those of the ATM options.
|
||
Exhibit 2.13 shows an example of 186-day options on AT&T Inc. (T),
|
||
their time value, and the corresponding vegas.
|
||
EXHIBIT 2.13 AT&T theos and vegas (T at $30, 186 days to Expry, 20%
|
||
IV).
|
||
Note that the 30-strike calls and puts have the highest time values. This
|
||
strike boasts the highest vega value, at 0.085. The lower the time premium,
|
||
the lower the vega—therefore, the less incremental IV changes affect the
|
||
option. Since higher-priced stocks have higher time premium (in absolute
|
||
terms, not necessarily in percentage terms) they will have higher vega.
|
||
Incidentally, if this were a $300 stock instead of a $30 stock, the 186-day
|
||
ATMs would have a 0.850 vega, if all other model inputs remain the same.
|
||
The Effect of Implied Volatility on Vega
|
||
The distribution of vega values among the strike prices shown in Exhibit
|
||
2.13 holds for a specific IV level. The vegas in Exhibit 2.13 were calculated
|
||
using a 20 percent IV. If a different IV were used in the calculation, the
|
||
relationship of the vegas to one another might change. Exhibit 2.14 shows
|
||
what the vegas would be at different IV levels.
|
||
EXHIBIT 2.14 Vega and IV.
|
||
Note in Exhibit 2.14 that at all three IV levels, the ATM strike maintains a
|
||
similar vega value. But the vegas of the ITM and OTM options can be
|
||
significantly different. Lower IV inputs tend to cause ITM and OTM vegas
|
||
to decline. Higher IV inputs tend to cause vegas to increase for ITMs and
|
||
OTMs.
|
||
The Effect of Time on Vega
|
||
As time passes, there is less time premium in the option that can be affected
|
||
by changes in IV. Consequently, vega gets smaller as expiration approaches.
|
||
Exhibit 2.15 shows the decreasing vega of a 50-strike call on a $50 stock
|
||
with a 25 percent IV as time to expiration decreases. Notice that as the
|
||
value of this ATM option decreases at its nonlinear rate of decay, the vega
|
||
decreases in a similar fashion.
|
||
EXHIBIT 2.15 The effect of time on vega.
|
||
|
||
Rho
|
||
One of my early jobs in the options business was clerking on the floor of
|
||
the Chicago Board of Trade in what was called the bond room. On one of
|
||
my first days on the job, the trader I worked for asked me what his position
|
||
was in a certain strike. I told him he was long 200 calls and long 300 puts.
|
||
“I’m long 500 puts?” he asked. “No,” I corrected, “you’re long 200 calls
|
||
and 300 puts.” At this point, he looked at me like I was from another planet
|
||
and said, “That’s 500. A put is a call; a call is a put.” That lesson was the
|
||
beginning of my journey into truly understanding options.
|
||
Put-Call Parity
|
||
Put and call values are mathematically bound together by an equation
|
||
referred to as put-call parity. In its basic form, put-call parity states:
|
||
where
|
||
c = call value,
|
||
PV(x) = present value of the strike price,
|
||
p = put value, and
|
||
s = stock price.
|
||
The put-call parity assumes that options are not exercised before
|
||
expiration (that is, that they are European style). This version of the put-call
|
||
parity is for European options on non-dividend-paying stocks. Put-call
|
||
parity can be modified to reflect the values of options on stocks that pay
|
||
dividends. In practice, equity-option traders look at the equation in a
|
||
slightly different way:
|
||
Traders serious about learning to trade options must know put-call parity
|
||
backward and forward. Why? First, by algebraically rearranging this
|
||
equation, it can be inferred that synthetically equivalent positions can be
|
||
established by simply adding stock to an option. Again, a put is a call; a call
|
||
is a put.
|
||
and
|
||
For example, a long call is synthetically equal to a long stock position
|
||
plus a long put on the same strike, once interest and dividends are figured
|
||
in. A synthetic long stock position is created by buying a call and selling a
|
||
put of the same month and strike. Understanding synthetic relationships is
|
||
intrinsic to understanding options. A more comprehensive discussion of
|
||
synthetic relationships and tactical considerations for creating synthetic
|
||
positions is offered in Chapter 6.
|
||
Put-call parity also aids in valuing options. If put-call parity shows a
|
||
difference in the value of the call versus the value of the put with the same
|
||
strike, there may be an arbitrage opportunity. That translates as “riskless
|
||
profit.” Buying the call and selling it synthetically (short put and short
|
||
stock) could allow a profit to be locked in if the prices are disparate.
|
||
Arbitrageurs tend to hold synthetic put and call prices pretty close together.
|
||
Generally, only professional traders can capture these types of profit
|
||
opportunities, by trading big enough positions to make very small profits (a
|
||
penny or less per contract sometimes) matter. Retail traders may be able to
|
||
take advantage of a disparity in put and call values to some extent, however,
|
||
by buying or selling the synthetic as a substitute for the actual option if the
|
||
position can be established at a better price synthetically.
|
||
Another reason that a working knowledge of put-call parity is essential is
|
||
that it helps attain a better understanding of how changes in the interest rate
|
||
affect option values. The greek rho measures this change. Rho is the rate of
|
||
change in an option’s value relative to a change in the interest rate.
|
||
Although some modeling programs may display this number differently,
|
||
most display a rho for the call and a rho for the put, both illustrating the
|
||
sensitivity to a one-percentage-point change in the interest rate. When the
|
||
interest rate rises by one percentage point, the value of the call increases by
|
||
the amount of its rho and the put decreases by the amount of its rho.
|
||
Likewise, when the interest rate decrease by one percentage point, the value
|
||
of the call decreases by its rho and the put increases by its rho. For example,
|
||
a call with a rho of 0.12 will increase $0.12 in value if the interest rate used
|
||
in the model is increased by one percentage point. Of course, interest rates
|
||
usually don’t rise or fall one percentage point in one day. More commonly,
|
||
rates will have incremental changes of 25 basis points. That means a call
|
||
with a 0.12 rho will theoretically gain $0.03 given an increase of 0.25
|
||
percentage points.
|
||
Mathematically, this change in option value as a product of a change in
|
||
the interest rate makes sense when looking at the formula for put-call parity.
|
||
and
|
||
|
||
But the change makes sense intuitively, too, when a call is considered as a
|
||
cheaper substitute for owning the stock. For example, compare a $100 stock
|
||
with a three-month 60-strike call on that same stock. Being so far ITM,
|
||
there would likely be no time value in the call. If the call can be purchased
|
||
at parity, which alternative would be a superior investment, the call for $40
|
||
or the stock for $100? Certainly, the call would be. It costs less than half as
|
||
much as the stock but has the same reward potential; and the $60 not spent
|
||
on the stock can be invested in an interest-bearing account. This interest
|
||
advantage adds value to the call. Raising the interest rate increases this
|
||
value, and lowering it decreases the interest component of the value of the
|
||
call.
|
||
A similar concept holds for puts. Professional traders often get a short-
|
||
stock rebate on proceeds from a short-stock sale. This is simply interest
|
||
earned on the capital received when the stock is shorted. Is it better to pay
|
||
interest on the price of a put for a position that gives short exposure or to
|
||
receive interest on the credit from shorting the stock? There is an interest
|
||
disadvantage to owning the put. Therefore, a rise in interest rates devalues
|
||
puts.
|
||
This interest effect becomes evident when comparing ATM call and put
|
||
prices. For example, with interest at 5 percent, three-month options on an
|
||
$80 stock that pays a $0.25 dividend before option expiration might look
|
||
something like this:
|
||
The ATM call is higher in theoretical value than the ATM put by $0.75.
|
||
That amount can be justified using put-call parity:
|
||
(Here, simple interest of $1 is calculated as 80 × 0.05 × [90 / 360] = 1.)
|
||
Changes in market conditions are kept in line by the put-call parity. For
|
||
example, if the price of the call rises because of an increase in IV, the price
|
||
of the put will rise in step. If the interest rate rises by a quarter of a
|
||
percentage point, from 5 percent to 5.25 percent, the interest calculated for
|
||
three months on the 80-strike will increase from $1 to $1.05, causing the
|
||
difference between the call and put price to widen. Another variable that
|
||
affects the amount of interest and therefore option prices is the time until
|
||
expiration.
|
||
The Effect of Time on Rho
|
||
The more time until expiration, the greater the effect interest rate changes
|
||
will have on options. In the previous example, a 25-basis-point change in
|
||
the interest rate on the 80-strike based on a three-month period caused a
|
||
change of 0.05 to the interest component of put-call parity. That is, 80 ×
|
||
0.0025 × (90/360) = 0.05. If a longer period were used in the example—say,
|
||
one year—the effect would be more profound; it will be $0.20: 80 × 0.0025
|
||
× (360/360) = 0.20. This concept is evident when the rhos of options with
|
||
different times to expiration are studied.
|
||
Exhibit 2.16 shows the rhos of ATM Procter & Gamble Co. (PG) calls
|
||
with various expiration months. The 750-day Long-Term Equity
|
||
AnticiPation Securities (LEAPS) have a rho of 0.858. As the number of
|
||
days until expiration decreases, rho decreases. The 22-day calls have a rho
|
||
of only 0.015. Rho is usually a fairly insignificant factor in the value of
|
||
short-term options, but it can come into play much more with long-term
|
||
option strategies involving LEAPS.
|
||
EXHIBIT 2.16 The effect of time on rho (Procter & Gamble @ $64.34)
|
||
|
||
Why the Numbers Don’t Don’t Always
|
||
Add Up
|
||
There will be many times when studying the rho of options in an option
|
||
chain will reveal seemingly counterintuitive results. To be sure, the numbers
|
||
don’t always add up to what appears logical. One reason for this is
|
||
rounding. Another is that traders are more likely to use simple interest in
|
||
calculating value, whereas the model uses compound interest. Hard-to-
|
||
borrow stocks and stocks involved in mergers and acquisitions may have
|
||
put-call parities that don’t work out right. But another, more common and
|
||
more significant fly in the ointment is early exercise.
|
||
Since the interest input in put-call parity is a function of the strike price, it
|
||
is reasonable to expect that the higher the strike price, the greater the effect
|
||
of interest on option prices will be. For European options, this is true to a
|
||
large extent, in terms of aggregate impact of interest on the call and put pair.
|
||
Strikes below the price where the stock is trading have a higher rho
|
||
associated with the call relative to the put, whereas strikes above the stock
|
||
price have a higher rho associated with the put relative to the call.
|
||
Essentially, the more in-the-money an option is, the higher its rho. But with
|
||
European options, observing the aggregate of the absolute values of the call
|
||
and put rhos would show a higher combined rho the higher the strike.
|
||
With American options, the put can be exercised early. A trader will
|
||
exercise a put before expiration if the alternative—being short stock and
|
||
receiving a short stock rebate—is a wiser choice based on the price of the
|
||
put. Professional traders may own stock as a hedge against a put. They may
|
||
exercise deep ITM puts (1.00-delta puts) to avoid paying interest on capital
|
||
charges related to the stock. The potential for early exercise is factored into
|
||
models that price American options. Here, when puts get deeper in-the-
|
||
money—that is, more apt to be exercised—the rho decreases. When the
|
||
strike price is very high relative to the stock price—meaning the put is very
|
||
deep ITM—and there is little or no time value left to the call or the put, the
|
||
aggregate put-call rho can be zero. Rho is discussed in greater detail in
|
||
Chapter 7.
|
||
THE GREEKS DEFINED
|
||
Delta (Δ) is:
|
||
1. The rate of change in an option’s value relative to a change in the underlying asset
|
||
price.
|
||
2. The derivative of the graph of an option’s value in relation to the underlying asset
|
||
price.
|
||
3. The equivalent of underlying asset represented by an option position.
|
||
4. The estimate of the likelihood of an option’s expiring in-the-money.
|
||
Gamma (Γ) is the rate of change in an option’s delta given a change in the price of the
|
||
underlying asset.
|
||
Theta (θ) is the rate of change in an option’s value given a unit change in the time to
|
||
expiration.
|
||
Vega is the rate of change in an option’s value relative to a change in implied volatility.
|
||
Rho (ρ) is the rate of change in an option’s value relative to a change in the interest rate.
|
||
Where to Find Option Greeks
|
||
There are many sources from which to obtain greeks. The Internet is an
|
||
excellent resource. Googling “option greeks” will display links to over four
|
||
million web pages, many of which have real-time greeks or an option
|
||
calculator. An option calculator is a simple interface that accepts the input
|
||
of the six variables to the model and yields a theoretical value and the
|
||
greeks for a single option.
|
||
Some web sites devoted to option education, such as
|
||
MarketTaker.com/option_modeling , have free calculators that can be used
|
||
for modeling positions and using the greeks.
|
||
In practice, many of the option-trading platforms commonly in use have
|
||
sophisticated analytics that involve greeks. Most options-friendly online
|
||
brokers provide trading platforms that enable traders to conduct
|
||
comprehensive manipulations of the greeks. For example, traders can look
|
||
at the greeks for their positions up or down one, two, or three standard
|
||
deviations. Or they can see what happens to their position greeks if IV or
|
||
time changes. With many trading platforms, position greeks are updated in
|
||
real time with changes in the stock price—an invaluable feature for active
|
||
traders.
|
||
Caveats with Regard to Online
|
||
Greeks
|
||
Often, online greeks are one click away, requiring little effort on the part of
|
||
the trader. Having greeks calculated automatically online is a quick and
|
||
convenient way to eyeball greeks for an option. But there is one major
|
||
problem with online greeks: reliability.
|
||
For active option traders, greeks are essential. There is no point in using
|
||
these figures if their accuracy cannot be assured. Experienced traders can
|
||
often spot these inaccuracies a proverbial mile away.
|
||
When looking at greeks from an online source that does not require you
|
||
to enter parameters into a model (as would be the case with professional
|
||
option-trading platforms), special attention needs to be paid to the
|
||
relationship of the option’s theoretical values to the bid and offer. One must
|
||
be cautious if the theoretical value of the option lies outside the bid-ask
|
||
spread. This scenario can exist for brief periods of time, but arbitrageurs
|
||
tend to prevent this from occurring routinely. If several options in a chain
|
||
all have theoretical values below the bid or above the offer, there is
|
||
probably a problem with one or more of the inputs used in the model.
|
||
Remember, an option-pricing model is just that: a model. It reflects what is
|
||
occurring in the market. It doesn’t tell where an option should be trading.
|
||
The complex changes that occur intraday in the market—taking the day
|
||
or weekend out, changes in stock price, volatility, and the interest rate—are
|
||
not always kept current. The user of the model must keep close watch. It’s
|
||
not reasonable to expect the computer to do the thinking for you.
|
||
Automatically calculated greeks can be used as a starting point. But before
|
||
using these figures in the decision-making process, the trader may have to
|
||
override the parameters that were used in the online calculation to make the
|
||
theos line up with market prices. Professional traders will ignore online
|
||
greeks altogether. They will use the greeks that are products of the inputs
|
||
they entered in their trading software. It comes down to this: if you want
|
||
something done right, do it yourself.
|
||
Thinking Greek
|
||
The challenge of trading option greeks is to adapt to thinking in terms of
|
||
delta, gamma, theta, vega, and rho. One should develop a feel for how
|
||
greeks react to changing market conditions. Greeks need to be monitored as
|
||
closely as and in some cases more closely than the option’s price itself. This
|
||
greek philosophy forms the foundation of option trading for active traders.
|
||
It offers a logical way to monitor positions and provides a medium in and of
|
||
itself to trade.
|
||
Notes
|
||
1 . Please note that definition 4 is not necessarily mathematically accurate.
|
||
This “trader’s definition” is included in the text because many option
|
||
traders use delta as a quick rule of thumb for estimating probability
|
||
without regard to the mathematical shortcomings of doing so.
|
||
2 . Note that the interest input in the equation is the interest, in dollars and
|
||
cents, on the strike. Technically, this would be calculated as compounded
|
||
interest, but in practice many traders use simple interest as a quick and
|
||
convenient way to do the calculation.
|
||
CHAPTER 3
|
||
Understanding Volatility
|
||
Most option strategies involve trading volatility in one way or another. It’s
|
||
easy to think of trading in terms of direction. But trading volatility?
|
||
Volatility is an abstract concept; it’s a different animal than the linear
|
||
trading paradigm used by most conventional market players. As an option
|
||
trader, it is essential to understand and master volatility.
|
||
Many traders trade without a solid understanding of volatility and its
|
||
effect on option prices. These traders are often unhappily surprised when
|
||
volatility moves against them. They mistake the adverse option price
|
||
movements that result from volatility for getting ripped off by the market
|
||
makers or some other market voodoo. Or worse, they surrender to the fact
|
||
that they simply don’t understand why sometimes these unexpected price
|
||
movements occur in options. They accept that that’s just the way it is.
|
||
Part of what gets in the way of a ready understanding of volatility is
|
||
context. The term volatility can have a few different meanings in the
|
||
options business. There are three different uses of the word volatility that an
|
||
option trader must be concerned with: historical volatility, implied
|
||
volatility, and expected volatility.
|
||
Historical Volatility
|
||
Imagine there are two stocks: Stock A and Stock B. Both are trading at
|
||
around $100 a share. Over the past month, a typical end-of-day net change
|
||
in the price of Stock A has been up or down $5 to $7. During that same
|
||
period, a typical daily move in Stock B has been something more like up or
|
||
down $1 or $2. Stock A has tended to move more than Stock B as a
|
||
percentage of its price, without regard to direction. Therefore, Stock A is
|
||
more volatile—in the common usage of the word—than Stock B. In the
|
||
options vernacular, Stock A has a higher historical volatility than Stock B.
|
||
Historical volatility (HV) is the annualized standard deviation of daily
|
||
returns. Also called realized volatility, statistical volatility , or stock
|
||
volatility , HV is a measure of how volatile the price movement of a
|
||
security has been during a certain period of time. But exactly how much
|
||
higher is Stock A’s HV than Stock B’s?
|
||
In order to objectively compare the volatilities of two stocks, historical
|
||
volatility must be quantified. HV relates this volatility information in an
|
||
objective numerical form. The volatility of a stock is expressed in terms of
|
||
standard deviation.
|
||
Standard Deviation
|
||
Although knowing the mathematical formula behind standard deviation is
|
||
not entirely necessary, understanding the concept is essential. Standard
|
||
deviation, sometimes represented by the Greek letter sigma (σ), is a
|
||
mathematical calculation that measures the dispersion of data from a mean
|
||
value. In this case, the mean is the average stock price over a certain period
|
||
of time. The farther from the mean the dispersion of occurrences (data) was
|
||
during the period, the greater the standard deviation.
|
||
Occurrences, in this context, are usually the closing prices of the stock.
|
||
Some utilizers of volatility data may use other inputs (a weighted average
|
||
of high, low, and closing prices, for example) in calculating standard
|
||
deviation. Close-to-close price data are the most commonly used.
|
||
The number of occurrences, a function of the time period, used in
|
||
calculating standard deviation may vary. Many online purveyors of this data
|
||
use the closing prices from the last 30 consecutive trading days to calculate
|
||
HV. Weekends and holidays are not factored into the equation since there is
|
||
no trading, and therefore no volatility, when the market isn’t open. After
|
||
each day, the oldest price is taken out of the calculation and replaced by the
|
||
most recent closing price. Using a shorter or longer period can yield
|
||
different results and can be useful in studying a stock’s volatility.
|
||
Knowing the number of days used in the calculation is crucial to
|
||
understanding what the output represents. For example, if the last 5 trading
|
||
days were extremely volatile, but the 25 days prior to that were
|
||
comparatively calm, the 5-day standard deviation would be higher than the
|
||
30-day standard deviation.
|
||
Standard deviation is stated as a percentage move in the price of the asset.
|
||
If a $100 stock has a standard deviation of 15 percent, a one-standard-
|
||
deviation move in the stock would be either $85 or $115—a 15 percent
|
||
move in either direction. Standard deviation is used for comparison
|
||
purposes. A stock with a standard deviation of 15 percent has experienced
|
||
bigger moves—has been more volatile—during the relevant time period
|
||
than a stock with a standard deviation of 6 percent.
|
||
When the frequency of occurrences are graphed, the result is known as a
|
||
distribution curve. There are many different shapes that a distribution curve
|
||
can take, depending on the nature of the data being observed. In general,
|
||
option-pricing models assume that stock prices adhere to a lognormal
|
||
distribution.
|
||
The shape of the distribution curve for stock prices has long been the
|
||
topic of discussion among traders and academics alike. Regardless of what
|
||
the true shape of the curve is, the concept of standard deviation applies just
|
||
the same. For the purpose of illustrating standard deviation, a normal
|
||
distribution is used here.
|
||
When the graph of data adheres to a normal distribution, the result is a
|
||
symmetrical bell-shaped curve. Standard deviation can be shown on the bell
|
||
curve to either side of the mean. Exhibit 3.1 represents a typical bell curve
|
||
with standard deviation.
|
||
EXHIBIT 3.1 Standard deviation.
|
||
Large moves in a security are typically less frequent than small ones.
|
||
Events that cause big changes in the price of a stock, like a company’s
|
||
being acquired by another or discovering its chief financial officer cooking
|
||
the books, are not a daily occurrence. Comparatively smaller price
|
||
fluctuations that reflect less extreme changes in the value of the corporation
|
||
are more typically seen day to day. Statistically, the most probable outcome
|
||
for a price change is found around the midpoint of the curve. What
|
||
constitutes a large move or a small move, however, is unique to each
|
||
individual security. For example, a two percent move in an index like the
|
||
Standard & Poor’s (S&P) 500 may be considered a big one-day move,
|
||
while a two percent move in a particularly active tech stock may be a daily
|
||
occurrence. Standard deviation offers a statistical explanation of what
|
||
constitutes a typical move.
|
||
In Exhibit 3.1 , the lines to either side of the mean represent one standard
|
||
deviation. About 68 percent of all occurrences will take place between up
|
||
one standard deviation and down one standard deviation. Two- and three-
|
||
standard-deviation values could be shown on the curve as well. About 95
|
||
percent of data occur between up and down two standard deviations and
|
||
about 99.7 percent between up and down three standard deviations. One
|
||
standard deviation is the relevant figure in determining historical volatility.
|
||
Standard Deviation and Historical
|
||
Volatility
|
||
When standard deviation is used in the context of historical volatility, it is
|
||
annualized to state what the one-year volatility would be. Historical
|
||
volatility is the annualized standard deviation of daily returns. This means
|
||
that if a stock is trading at $100 a share and its historical volatility is 10
|
||
percent, then about 68 percent of the occurrences (closing prices) are
|
||
expected to fall between $90 and $110 during a one-year period (based on
|
||
recent past performance).
|
||
Simply put, historical volatility shows how volatile a stock has been
|
||
based on price movements that have occurred in the past. Although option
|
||
traders may study HV to make informed decisions as to the value of options
|
||
traded on a stock, it is not a direct function of option prices. For this, we
|
||
must look to implied volatility.
|
||
Implied Volatility
|
||
Volatility is one of the six inputs of an option-pricing model. Some of the
|
||
other inputs—strike price, stock price, the number of days until expiration,
|
||
and the current interest rate—are easily observable. Past dividend policy
|
||
allows an educated guess as to what the dividend input should be. But
|
||
where can volatility be found?
|
||
As discussed in Chapter 2, the output of the pricing model—the option’s
|
||
theoretical value—in practice is not necessarily an output at all. When
|
||
option traders use the pricing model, they commonly substitute the actual
|
||
price at which the option is trading for the theoretical value. A value in the
|
||
middle of the bid-ask spread is often used. The pricing model can be
|
||
considered to be a complex algebra equation in which any variable can be
|
||
solved for. If the theoretical value is known—which it is—it along with the
|
||
five known inputs can be combined to solve for the unknown volatility.
|
||
Implied volatility (IV) is the volatility input in a pricing model that, in
|
||
conjunction with the other inputs, returns the theoretical value of an option
|
||
matching the market price.
|
||
For a specific stock price, a given implied volatility will yield a unique
|
||
option value. Take a stock trading at $44.22 that has the 60-day 45-strike
|
||
call at a theoretical value of $1.10 with an 18 percent implied volatility
|
||
level. If the stock price remains constant, but IV rises to 19 percent, the
|
||
value of the call will rise by its vega, which in this case is about 0.07. The
|
||
new value of the call will be $1.17. Raising IV another point, to 20 percent,
|
||
raises the theoretical value by another $0.07, to $1.24. The question is:
|
||
What would cause implied volatility to change?
|
||
Supply and Demand: Not Just a Good
|
||
Idea, It’s the Law!
|
||
Options are an excellent vehicle for speculation. However, the existence of
|
||
the options market is better justified by the primary economic purpose of
|
||
options: as a risk management tool. Hedgers use options to protect their
|
||
assets from adverse price movements, and when the perception of risk
|
||
increases, so does demand for this protection. In this context, risk means
|
||
volatility—the potential for larger moves to the upside and downside. The
|
||
relative prices of options are driven higher by increased demand for
|
||
protective options when the market anticipates greater volatility. And option
|
||
prices are driven lower by greater supply—that is, selling of options—when
|
||
the market expects lower volatility. Like those of all assets, option prices
|
||
are subject to the law of supply and demand.
|
||
When volatility is expected to rise, demand for options is not limited to
|
||
hedgers. Speculative traders would arguably be more inclined to buy a call
|
||
than to buy the stock if they are bullish but expect future volatility to be
|
||
high. Calls require a lower cash outlay. If the stock moves adversely, there
|
||
is less capital at risk, but still similar profit potential.
|
||
When volatility is expected to be low, hedging investors are less inclined
|
||
to pay for protection. They are more likely to sell back the options they may
|
||
have bought previously to recoup some of the expense. Options are a
|
||
decaying asset. Investors are more likely to write calls against stagnant
|
||
stocks to generate income in anticipated low-volatility environments.
|
||
Speculative traders will implement option-selling strategies, such as short
|
||
strangles or iron condors, in an attempt to capitalize on stocks they believe
|
||
won’t move much. The rising supply of options puts downward pressure on
|
||
option prices.
|
||
Many traders sum up IV in two words: fear and greed . When option
|
||
prices rise and fall, not because of changes in the stock price, time to
|
||
expiration, interest rates, or dividends, but because of pure supply and
|
||
demand, it is implied volatility that is the varying factor. There are many
|
||
contributing factors to traders’ willingness to demand or supply options.
|
||
Anticipation of events such as earnings reports, Federal Reserve
|
||
announcements, or the release of other news particular to an individual
|
||
stock can cause anxiety, or fear, in traders and consequently increase
|
||
demand for options that causes IV to rise. IV can fall when there is
|
||
complacency in the market or when the anticipated news has been
|
||
announced and anxiety wanes. “Buy the rumor, sell the news” is often
|
||
reflected in option implied volatility. When there is little fear of market
|
||
movement, traders use options to squeeze out more profits—greed.
|
||
Arbitrageurs, such as market makers who trade delta neutral—a strategy
|
||
that will be discussed further in Chapters 12 and 13—must be relentlessly
|
||
conscious of implied volatility. When immediate directional risk is
|
||
eliminated from a position, IV becomes the traded commodity. Arbitrageurs
|
||
who focus their efforts on trading volatility (colloquially called vol traders )
|
||
tend to think about bids and offers in terms of IV. In the mind of a vol
|
||
trader, option prices are translated into volatility levels. A trader may look at
|
||
a particular option and say it is 30 bid at 31 offer. These values do not
|
||
represent the prices of the options but rather the corresponding implied
|
||
volatilities. The meaning behind the trader’s remark is that the market is
|
||
willing to buy implied volatility at 30 percent and sell it at 31 percent. The
|
||
actual prices of the options themselves are much less relevant to this type of
|
||
trader.
|
||
Should HV and IV Be the Same?
|
||
Most option positions have exposure to volatility in two ways. First, the
|
||
profitability of the position is usually somewhat dependent on movement
|
||
(or lack of movement) of the underlying security. This is exposure to HV.
|
||
Second, profitability can be affected by changes in supply and demand for
|
||
the options. This is exposure to IV. In general, a long option position
|
||
benefits when volatility—both historical and implied—increases. A short
|
||
option position benefits when volatility—historical and implied—decreases.
|
||
That said, buying options is buying volatility and selling options is selling
|
||
volatility.
|
||
The Relationship of HV and IV
|
||
It’s intuitive that there should exist a direct relationship between the HV and
|
||
IV. Empirically, this is often the case. Supply and demand for options, based
|
||
on the market’s expectations for a security’s volatility, determines IV.
|
||
It is easy to see why IV and HV often act in tandem. But, although HV
|
||
and IV are related, they are not identical. There are times when IV and HV
|
||
move in opposite directions. This is not so illogical, if one considers the key
|
||
difference between the two: HV is calculated from past stock price
|
||
movements; it is what has happened. IV is ultimately derived from the
|
||
market’s expectation for future volatility.
|
||
If a stock typically has an HV of 30 percent and nothing is expected to
|
||
change, it can be reasonable to expect that in the future the stock will
|
||
continue to trade at a 30 percent HV. By that logic, assuming that nothing is
|
||
expected to change, IV should be fairly close to HV. Market conditions do
|
||
change, however. These changes are often regular and predictable. Earnings
|
||
reports are released once a quarter in many stocks, Federal Open Market
|
||
Committee meetings happen regularly, and dates of other special
|
||
announcements are often disclosed to the public in advance. Although the
|
||
outcome of these events cannot be predicted, when they will occur often
|
||
can be. It is around these widely anticipated events that HV-IV divergences
|
||
often occur.
|
||
HV-IV Divergence
|
||
An HV-IV divergence occurs when HV declines and IV rises or vice versa.
|
||
The classic example is often observed before a company’s quarterly
|
||
earnings announcement, especially when there is lack of consensus among
|
||
analysts’ estimates. This scenario often causes HV to remain constant or
|
||
decline while IV rises. The reason? When there is a great deal of
|
||
uncertainty as to what the quarterly earnings will be, investors are reluctant
|
||
to buy or sell the stock until the number is released. When this happens, the
|
||
stock price movement (volatility) consolidates, causing the calculated HV
|
||
to decline. IV, however, can rise as traders scramble to buy up options—
|
||
bidding up their prices. When the news is out, the feared (or hoped for)
|
||
move in the stock takes place (or doesn’t), and HV and IV tend to converge
|
||
again.
|
||
Expected Volatility
|
||
Whether trading options or stocks, simple or complex strategies, traders
|
||
must consider volatility. For basic buy-and-hold investors, taking a potential
|
||
investment’s volatility into account is innate behavior. Do I buy
|
||
conservative (nonvolatile) stocks or more aggressive (volatile) stocks?
|
||
Taking into account volatility, based not just on a gut feeling but on hard
|
||
numbers, can lead to better, more objective trading decisions.
|
||
Expected Stock Volatility
|
||
Option traders must have an even greater focus on volatility, as it plays a
|
||
much bigger role in their profitability—or lack thereof. Because options can
|
||
create highly leveraged positions, small moves can yield big profits or
|
||
losses. Option traders must monitor the likelihood of movement in the
|
||
underlying closely. Estimating what historical volatility (standard deviation)
|
||
will be in the future can help traders quantify the probability of movement
|
||
beyond a certain price point. This leads to better decisions about whether to
|
||
enter a trade, when to adjust a position, and when to exit.
|
||
There is no way of knowing for certain what the future holds. But option
|
||
data provide traders with tools to develop expectations for future stock
|
||
volatility. IV is sometimes interpreted as the market’s estimate of the future
|
||
volatility of the underlying security. That makes it a ready-made estimation
|
||
tool, but there are two caveats to bear in mind when using IV to estimate
|
||
future stock volatility.
|
||
The first is that the market can be wrong. The market can wrongly price
|
||
stocks. This mispricing can lead to a correction (up or down) in the prices
|
||
of those stocks, which can lead to additional volatility, which may not be
|
||
priced in to the options. Although there are traders and academics believe
|
||
that the option market is fairly efficient in pricing volatility, there is a room
|
||
for error. There is the possibility that the option market can be wrong.
|
||
Another caveat is that volatility is an annualized figure—the annualized
|
||
standard deviation. Unless the IV of a LEAPS option that has exactly one
|
||
year until expiration is substituted for the expected volatility of the
|
||
underlying stock over exactly one year, IV is an incongruent estimation for
|
||
the future stock volatility. In practice, the IV of an option must be adjusted
|
||
to represent the period of time desired.
|
||
There is a common technique for deannualizing IV used by professional
|
||
traders and retail traders alike. 1 The first step in this process to deannualize
|
||
IV is to turn it into a one-day figure as opposed to one-year figure. This is
|
||
accomplished by dividing IV by the square root of the number of trading
|
||
days in a year. The number many traders use to approximate the number of
|
||
trading days per year is 256, because its square root is a round number: 16.
|
||
The formula is
|
||
For example, a $100 stock that has an at-the-money (ATM) call trading at
|
||
a 32 percent volatility implies that there is about a 68 percent chance that
|
||
the underlying stock will be between $68 and $132 in one year’s time—
|
||
that’s $100 ± ($100 × 0.32). The estimation for the market’s expectation for
|
||
the volatility of the stock for one day in terms of standard deviation as a
|
||
percentage of the price of the underlying is computed as follows:
|
||
In one day’s time, based on an IV of 32 percent, there is a 68 percent
|
||
chance of the stock’s being within 2 percent of the stock price—that’s
|
||
between $98 and $102.
|
||
There may be times when it is helpful for traders to have a volatility
|
||
estimation for a period of time longer than one day—a week or a month, for
|
||
example. This can be accomplished by multiplying the one-day volatility by
|
||
the square root of the number of trading days in the relevant period. The
|
||
equation is as follows:
|
||
If the period in question is one month and there are 22 business days
|
||
remaining in that month, the same $100 stock with the ATM call trading at a
|
||
32 percent implied volatility would have a one-month volatility of 9.38
|
||
percent.
|
||
Based on this calculation for one month, it can be estimated that there is a
|
||
68 percent chance of the stock’s closing between $90.62 and $109.38 based
|
||
on an IV of 32 percent.
|
||
Expected Implied Volatility
|
||
Although there is a great deal of science that can be applied to calculating
|
||
expected actual volatility, developing expectations for implied volatility is
|
||
more of an art. This element of an option’s price provides more risk and
|
||
more opportunity. There are many traders who make their living distilling
|
||
direction out of their positions and trading implied volatility. To be
|
||
successful, a trader must forecast IV.
|
||
Conceptually, trading IV is much like trading anything else. A trader who
|
||
thinks a stock is going to rise will buy the stock. A trader who thinks IV is
|
||
going to rise will buy options. Directional stock traders, however, have
|
||
many more analysis tools available to them than do vol traders. Stock
|
||
traders have both technical analysis (TA) and fundamental analysis at their
|
||
disposal.
|
||
Technical Analysis
|
||
There are scores, perhaps hundreds, of technical tools for analyzing stocks,
|
||
but there are not many that are available for analyzing IV. Technical
|
||
analysis is the study of market data, such as past prices or volume, which is
|
||
manipulated in such a way that it better illustrates market activity. TA
|
||
studies are usually represented graphically on a chart.
|
||
Developing TA tools for IV is more of a challenge than it is for stocks.
|
||
One reason is that there is simply a lot more data to manage—for each
|
||
stock, there may be hundreds of options listed on it. The only practical way
|
||
of analyzing options from a TA standpoint is to use implied volatility. IV is
|
||
more useful than raw historical option prices themselves. Information for
|
||
both IV and HV is available in the form of volatility charts, or vol charts.
|
||
(Vol charts are discussed in detail in Chapter 14.) Volatility charts are
|
||
essential for analyzing options because they give more complete
|
||
information.
|
||
To get a clear picture of what is going on with the price of an option (the
|
||
goal of technical analysis for any asset), just observing the option price does
|
||
not supply enough information for a trader to work with. It’s incomplete.
|
||
For example, if a call rises in value, why did it rise? What greek contributed
|
||
to its value increase? Was it delta because the underlying stock rose? Or
|
||
was it vega because volatility rose? How did time decay factor in? Using a
|
||
volatility chart in conjunction with a conventional stock chart (and being
|
||
aware of time decay) tells the whole, complete, story.
|
||
Another reason historical option prices are not used in TA is the option
|
||
bid-ask spread. For most stocks, the difference between the bid and the ask
|
||
is equal to a very small percentage of the stock’s price. Because options are
|
||
highly leveraged instruments, their bid-ask width can equal a much higher
|
||
percentage of the price.
|
||
If a trader uses the last trade to graph an option’s price, it could look as if
|
||
a very large percentage move has occurred when in fact it has not. For
|
||
example, if the option trades a small contract size on the bid (0.80), then on
|
||
the offer (0.90) it would appear that the option rose 12.5 percent in value.
|
||
This large percentage move is nothing more than market noise. Using
|
||
volatility data based off the midpoint-of-the-market theoretical value
|
||
eliminates such noise.
|
||
Fundamental Analysis
|
||
Fundamental analysis can have an important role in developing
|
||
expectations for IV. Fundamental analysis is the study of economic factors
|
||
that affect the value of an asset in order to determine what it is worth. With
|
||
stocks, fundamental analysis may include studying income statements,
|
||
balance sheets, and earnings reports. When the asset being studied is IV,
|
||
there are fewer hard facts available. This is where the art of analyzing
|
||
volatility comes into play.
|
||
Essentially, the goal is to understand the psychology of the market in
|
||
relation to supply and demand for options. Where is the fear? Where is the
|
||
complacency? When are news events anticipated? How important are they?
|
||
Ultimately, the question becomes: what is the potential for movement in the
|
||
underlying? The greater the chance of stock movement, the more likely it is
|
||
that IV will rise. When unexpected news is announced, IV can rise quickly.
|
||
The determination of the fundamental relevance of surprise announcements
|
||
must be made quickly.
|
||
Unfortunately, these questions are subjective in nature. They require the
|
||
trader to apply intuition and experience on a case-by-case basis. But there
|
||
are a few observations to be made that can help a trader make better-
|
||
educated decisions about IV.
|
||
Reversion to the Mean
|
||
The IVs of the options on many stocks and indexes tend to trade in a range
|
||
unique to those option classes. This is referred to as the mean—or average
|
||
—volatility level. Some securities will have smaller mean IV ranges than
|
||
others. The range being observed should be established for a period long
|
||
enough to confirm that it is a typical IV for the security, not just a
|
||
temporary anomaly. Traders should study IV over the most recent 6-month
|
||
period. When IV has changed significantly during that period, a 12-month
|
||
study may be necessary. Deviations from this range, either above or below
|
||
the established mean range, will occur from time to time. When following a
|
||
breakout from the established range, it is common for IV to revert back to
|
||
its normal range. This is commonly called reversion to the mean among
|
||
volatility watchers.
|
||
The challenge is recognizing when things change and when they stay the
|
||
same. If the fundamentals of the stock change in such a way as to give the
|
||
options market reason to believe the stock will now be more or less volatile
|
||
on an ongoing basis than it typically has been in the recent past, the IV may
|
||
not revert to the mean. Instead, a new mean volatility level may be
|
||
established.
|
||
When considering the likelihood of whether IV will revert to recent levels
|
||
after it has deviated or find a new range, the time horizon and changes in
|
||
the marketplace must be taken into account. For example, between 1998
|
||
and 2003 the mean volatility level of the SPX was around 20 percent to 30
|
||
percent. By the latter half of 2006, the mean IV was in the range of 10
|
||
percent to 13 percent. The difference was that between 1998 and 2003 was
|
||
the buildup of “the tech bubble,” as it was called by the financial media.
|
||
Market volatility ultimately leveled off in 2003.
|
||
In a later era, between the fall of 2010 and late summer of 2011 SPX
|
||
implied volatility settled in to trade mostly between 12 and 20 percent. But
|
||
in August 2011, as the European debt crisis heated up, a new, more volatile
|
||
range between 24 and 40 percent reigned for some time.
|
||
No trader can accurately predict future IV any more than one can predict
|
||
the future price of a stock. However, with IV there are often recurring
|
||
patterns that traders can observe, like the ebb and flow of IV often
|
||
associated with earnings or other regularly scheduled events. But be aware
|
||
that the IV’s rising before the last 15 earnings reports doesn’t mean it will
|
||
this time.
|
||
CBOE Volatility Index
|
||
®
|
||
Often traders look to the implied volatility of the market as a whole for
|
||
guidance on the IV of individual stocks. Traders use the Chicago Board
|
||
Options Exchange (CBOE) Volatility Index® , or VIX® , as an indicator of
|
||
overall market volatility.
|
||
When people talk about the market, they are talking about a broad-based
|
||
index covering many stocks on many diverse industries. Usually, they are
|
||
referring to the S&P 500. Just as the IV of a stock may offer insight about
|
||
investors’ feelings about that stock’s future volatility, the volatility of
|
||
options on the S&P 500—SPX options—may tell something about the
|
||
expected volatility of the market as a whole.
|
||
VIX is an index published by the Chicago Board Options Exchange that
|
||
measures the IV of a hypothetical 30-day option on the SPX. A 30-day
|
||
option on the SPX only truly exists once a month—30 days before
|
||
expiration. CBOE computes a hypothetical 30-day option by means of a
|
||
weighted average of the two nearest-term months.
|
||
When the S&P 500 rises or falls, it is common to see individual stocks
|
||
rise and fall in sympathy with the index. Most stocks have some degree of
|
||
market risk. When there is a perception of higher risk in the market as a
|
||
whole, there can consequently be a perception of higher risk in individual
|
||
stocks. The rise or fall of the IV of SPX can translate into the IV of
|
||
individual stocks rising or falling.
|
||
Implied Volatility and Direction
|
||
Who’s afraid of falling stock prices? Logically, declining stocks cause
|
||
concern for investors in general. There is confirmation of that statement in
|
||
the options market. Just look at IV. With most stocks and indexes, there is
|
||
an inverse relationship between IV and the underlying price. Exhibit 3.2
|
||
shows the SPX plotted against its 30-day IV, or the VIX.
|
||
EXHIBIT 3.2 SPX vs. 30-day IV (VIX).
|
||
The heavier line is the SPX, and the lighter line is the VIX. Note that as
|
||
the price of SPX rises, the VIX tends to decline and vice versa. When the
|
||
market declines, the demand for options tends to increase. Investors hedge
|
||
by buying puts. Traders speculate on momentum by buying puts and
|
||
speculate on a turnaround by buying calls. When the market moves higher,
|
||
investors tend to sell their protection back and write covered calls or cash-
|
||
secured puts. Option speculators initiate option-selling strategies. There is
|
||
less fear when the market is rallying.
|
||
This inverse relationship of IV to the price of the underlying is not unique
|
||
to the SPX; it applies to most individual stocks as well. When a stock
|
||
moves lower, the market usually bids up IV, and when the stock rises, the
|
||
market tends to offer IV creating downward pressure.
|
||
Calculating Volatility Data
|
||
Accurate data are essential for calculating volatility. Many of the volatility
|
||
data that are readily available are useful, but unfortunately, some are not.
|
||
HV is a value that is easily calculated from publicly accessible past closing
|
||
prices of a stock. It’s rather straightforward. Traders can access HV from
|
||
many sources. Retail traders often have access to HV from their brokerage
|
||
firm. Trading firms or clearinghouses often provide professional traders
|
||
with HV data. There are some excellent online resources for HV as well.
|
||
HV is a calculation with little subjectivity—the numbers add up how they
|
||
add up. IV, however, can be a bit more ambiguous. It can be calculated
|
||
different ways to achieve different desired outcomes; it is user-centric. Most
|
||
of the time, traders consider the theoretical value to be between the bid and
|
||
the ask prices. On occasion, however, a trader will calculate IV for the bid,
|
||
the ask, the last trade price, or, sometimes, another value altogether. There
|
||
may be a valid reason for any of these different methods for calculating IV.
|
||
For example, if a trader is long volatility and aspires to reduce his position,
|
||
calculating the IV for the bid shows him what IV level can be sold to
|
||
liquidate his position.
|
||
Firms, online data providers, and most options-friendly brokers offer IV
|
||
data. Past IV data is usually displayed graphically in what is known as a
|
||
volatility chart or vol chart. Current IV is often displayed along with other
|
||
data right in the option chain. One note of caution: when the current IV is
|
||
displayed, however, it should always be scrutinized carefully. Was the bid
|
||
used in calculating this figure? What about the ask? How long ago was this
|
||
calculation made? There are many questions that determine the accuracy of
|
||
a current IV, and rarely are there any answers to support the number.
|
||
Traders should trust only IV data they knowingly generated themselves
|
||
using a pricing model.
|
||
Volatility Skew
|
||
There are many platforms (software or Web-based) that enable traders to
|
||
solve for volatility values of multiple options within the same option class.
|
||
Values of options of the same class are interrelated. Many of the model
|
||
parameters are shared among the different series within the same class. But
|
||
IV can be different for different options within the same class. This is
|
||
referred to as the volatility skew . There are two types of volatility skew:
|
||
term structure of volatility and vertical skew.
|
||
Term Structure of Volatility
|
||
Term structure of volatility—also called monthly skew or horizontal skew
|
||
—is the relationship among the IVs of options in the same class with the
|
||
same strike but with different expiration months. IV, again, is often
|
||
interpreted as the market’s estimate of future volatility. It is reasonable to
|
||
assume that the market will expect some months to be more volatile than
|
||
others. Because of this, different expiration cycles can trade at different IVs.
|
||
For example, if a company involved in a major product-liability lawsuit is
|
||
expecting a verdict on the case to be announced in two months, the one-
|
||
month IV may be low, as the stock is not expected to move much until the
|
||
suit is resolved. The two-month volatility may be much higher, however,
|
||
reflecting the expectations of a big move in the stock up or down,
|
||
depending on the outcome.
|
||
The term structure of volatility also varies with the normal ebb and flow
|
||
of volatility within the business cycle. In periods of declining volatility, it is
|
||
common for the month with the least amount of time until expiration, also
|
||
known as the front month, to trade at a lower volatility than the back
|
||
months, or months with more time until expiration. Conversely, when
|
||
volatility is rising, the front month tends to have a higher IV than the back
|
||
months.
|
||
Exhibit 3.3 shows historical option prices and their corresponding IVs for
|
||
32.5-strike calls on General Motors (GM) during a period of low volatility.
|
||
EXHIBIT 3.3 GM term structure of volatility.
|
||
In this example, no major news is expected to be released on GM, and
|
||
overall market volatility is relatively low. The February 32.5 call has the
|
||
lowest IV, at 32 percent. Each consecutive month has a higher IV than the
|
||
previous month. A graduated increasing or decreasing IV for each
|
||
consecutive expiration cycle is typical of the term structure of volatility.
|
||
Under normal circumstances, the front month is the most sensitive to
|
||
changes in IV. There are two reasons for this. First, front-month options are
|
||
typically the most actively traded. There is more buying and selling
|
||
pressure. Their IV is subject to more activity. Second, vegas are smaller for
|
||
options with fewer days until expiration. This means that for the same
|
||
monetary change in an option’s value, the IV needs to move more for short-
|
||
term options.
|
||
Exhibit 3.4 shows the same GM options and their corresponding vegas.
|
||
EXHIBIT 3.4 GM vegas.
|
||
If the value of the September 32.5 calls increases by $0.10, IV must rise
|
||
by 1 percentage point. If the February 32.5 calls increase by $0.10, IV must
|
||
rise 3 percentage points. As expiration approaches, the vega gets even
|
||
smaller. With seven days until expiration, the vega would be about 0.014.
|
||
This means IV would have to change about 7 points to change the call value
|
||
$0.10.
|
||
Vertical Skew
|
||
The second type of skew found in option IV is vertical skew, or strike skew.
|
||
Vertical skew is the disparity in IV among the strike prices within the same
|
||
month for an option class. The options on most stocks and indexes
|
||
experience vertical skew. As a general rule, the IV of downside options—
|
||
calls and puts with strike prices lower than the at-the-money (ATM) strike
|
||
—trade at higher IVs than the ATM IV. The IV of upside options—calls and
|
||
puts with strike prices higher than the ATM strike—typically trade at lower
|
||
IVs than the ATM IV.
|
||
The downside is often simply referred to as puts and the upside as calls.
|
||
The rationale for this lingo is that OTM options (puts on the downside and
|
||
calls on the upside) are usually more actively traded than the ITM options.
|
||
By put-call parity, a put can be synthetically created from a call, and a call
|
||
can be synthetically created from a put simply by adding the appropriate
|
||
long or short stock position.
|
||
Exhibit 3.5 shows the vertical skew for 86-day options on Citigroup Inc.
|
||
(C) on a typical day, with IVs rounded to the nearest tenth.
|
||
EXHIBIT 3.5 Citigroup vertical skew.
|
||
Notice the IV of the puts (downside options) is higher than that of the
|
||
calls (upside options), with the 31 strike’s volatility more than 10 points
|
||
higher than that of the 38 strike. Also, the difference in IV per unit change
|
||
in the strike price is higher for the downside options than it is for the upside
|
||
ones. The difference between the IV of the 31 strike is 2 full points higher
|
||
than the 32 strike, which is 1.8 points higher than the 33 strike. But the 36
|
||
strike’s IV is only 1.1 points higher than the 37 strike, which is also just 1.1
|
||
points higher than the 38 strike.
|
||
This incremental difference in the IV per strike is often referred to as the
|
||
slope. The puts of most underlyings tend to have a greater slope to their
|
||
skew than the calls. Many models allow values to be entered for the upside
|
||
slope and the downside slope that mathematically increase or decrease IVs
|
||
of each strike incrementally. Some traders believe the slope should be a
|
||
straight line, while others believe it should be an exponentially sloped line.
|
||
If the IVs were graphed, the shape of the skew would vary among asset
|
||
classes. This is sometimes referred to as the volatility smile or sneer,
|
||
depending on the shape of the IV skew. Although Exhibit 3.5 is a typical
|
||
paradigm for the slope for stock options, bond options and other commodity
|
||
options would have differently shaped skews. For example, grain options
|
||
commonly have calls with higher IVs than the put IVs.
|
||
Volatility skew is dependent on supply and demand. Greater demand for
|
||
downside protection may cause the overall IV to rise, but it can cause the
|
||
IV of puts to rise more relative to the calls or vice versa. There are many
|
||
traders who make their living trading volatility skew.
|
||
Note
|
||
1 . This technique provides only an estimation of future volatility.
|
||
CHAPTER 4
|
||
Option-Specific Risk and Opportunity
|
||
New endeavors can be intimidating. The first day at a new job or new
|
||
school is a challenge. Option trading is no different. When traders first
|
||
venture into the world of options, they tend to start with what they know—
|
||
trading direction. Buying stocks is at the heart of the comfort zone for many
|
||
traders. Buying a call as a substitute for buying a stock is a logical
|
||
progression. And for the most part, call buying is a pretty straightforward
|
||
way to take a bullish position in a stock. But it’s not just a bullish position.
|
||
The greeks come into play with the long call, providing both risk and
|
||
opportunity.
|
||
Long ATM Call
|
||
Kim is a trader who is bullish on the Walt Disney Company (DIS) over the
|
||
short term. The time horizon of her forecast is three weeks. Instead of
|
||
buying 100 shares of Disney at $35.10 per share, Kim decides to buy one
|
||
Disney March 35 call at $1.10. In this example, March options have 44
|
||
days until expiration. How can Kim profit from this position? How can she
|
||
lose?
|
||
Exhibit 4.1 shows the profit and loss (P&(L)) for the call at different time
|
||
periods. The top line is when the trade is executed; the middle, dotted line is
|
||
after three weeks have passed; and the bottom, darker line is at expiration.
|
||
Kim wants Disney to rise in price, which is evident by looking at the graph
|
||
for any of the three time horizons. She would anticipate a loss if the stock
|
||
price declines. These expectations are related to the position’s delta, but that
|
||
is not the only risk exposure Kim has. As indicated by the three different
|
||
lines in Exhibit 4.1 , the call loses value over time. This is called theta risk .
|
||
She has other risk exposure as well. Exhibit 4.2 lists the greeks for the DIS
|
||
March 35 call.
|
||
EXHIBIT 4.1 P&(L) of Disney 35 call.
|
||
EXHIBIT 4.2 Greeks for 35 Disney call.
|
||
Delta 0.57
|
||
Gamma0.166
|
||
Theta −0.013
|
||
Vega 0.048
|
||
Rho 0.023
|
||
Kim’s immediate directional exposure is quantified by the delta, which is
|
||
0.57. Delta is immediate directional exposure because it’s subject to change
|
||
by the amount of the gamma. The positive gamma of this position helps
|
||
Kim by increasing the delta as Disney rises and decreasing it as it falls.
|
||
Kim, however, has time working against her—theta. At this point, she
|
||
theoretically loses $0.013 per day. Since her call is close to being at-the-
|
||
money, she would anticipate her theta becoming more negative as
|
||
expiration approaches if Disney’s share price remains unchanged. She also
|
||
has positive vega exposure. A one-percentage-point increase in implied
|
||
volatility (IV) earns Kim just under $0.05. A one-point decrease costs her
|
||
about $0.05. With so few days until expiration, the 35-strike call has very
|
||
little rho exposure. A full one-percentage-point change in the interest rate
|
||
changes her call’s value by only $0.023.
|
||
Delta
|
||
Some of Kim’s risks warrant more concern than others. With this position,
|
||
delta is of the greatest concern, followed by theta. Kim expects the call to
|
||
rise in value and accepts the risk of decline. Delta exposure was her main
|
||
rationale for establishing the position. She expects to hold it for about three
|
||
weeks. Kim is willing to accept the trade-off of delta exposure for theta,
|
||
which will cost her three weeks of erosion of option premium. If the
|
||
anticipated delta move happens sooner than expected, Kim will have less
|
||
decay. Exhibit 4.3 shows the value of her 35 call at various stock prices
|
||
over time. The left column is the price of Disney. The top row is the number
|
||
of days until expiration.
|
||
EXHIBIT 4.3 Disney 35 call price–time matrix–value.
|
||
The effect of delta is evident as the stock rises or falls. When the position
|
||
is established (44 days until expiration), the change in the option price if the
|
||
stock were to move from $35 to $36 is 0.62 (1.66 − 1.04). Between stock
|
||
prices of $36 and $37, the option gains 0.78 (2.44 −1.66). If the stock were
|
||
to decline in value from $35 to $34, the option loses 0.47 (1.04 − 0.57). The
|
||
option gains value at a faster rate as the stock rises and loses value at a
|
||
slower rate as the stock falls. This is the effect of gamma.
|
||
Gamma
|
||
With this type of position, gamma is an important but secondary
|
||
consideration. Gamma is most helpful to Kim in developing expectations of
|
||
what the delta will be as the stock price rises or falls. Exhibit 4.4 shows the
|
||
delta at various stock prices over time.
|
||
EXHIBIT 4.4 Disney call price–time matrix–delta.
|
||
Kim pays attention to gamma only to gauge her delta. Why is this
|
||
important to her? In this trade, Kim is focused on direction. Knowing how
|
||
much her call will rise or fall in step with the stock is her main concern.
|
||
Notice that her delta tends to get bigger as the stock rises and smaller as the
|
||
stock falls. As time passes, the delta gravitates toward 1.00 or 0, depending
|
||
on whether the call is in-the-money (ITM) or out-of-the-money (OTM).
|
||
Theta
|
||
Option buying is a veritable race against the clock. With each passing day,
|
||
the option loses theoretical value. Refer back to Exhibit 4.3 . When three
|
||
weeks pass and the time to expiration decreases from 44 days to 23, what
|
||
happens to the call value? If the stock price stays around its original level,
|
||
theta will be responsible for a loss of about 30 percent of the premium. If
|
||
Disney is at $35 with 23 days to expiration, the call will be worth $0.73.
|
||
With a big enough move in either direction, however, theta matters much
|
||
less.
|
||
With 23 days to expiration and Disney at $39, there is only 0.12 of time
|
||
value—the premium paid over parity for the option. At that point, it is
|
||
almost all delta exposure. Similarly, if the Disney stock price falls after
|
||
three weeks to $33, the call will have only 0.10 of time value. Time decay is
|
||
the least of Kim’s concerns if the stock makes a big move.
|
||
Vega
|
||
After delta and theta, vega is the next most influential contributor to Kim’s
|
||
profit or peril. With Disney at $35.10, the 1.10 premium for the 35-strike
|
||
call represents $1 of time value—all of which is vulnerable to changes in
|
||
IV. The option’s 1.10 value returns an IV of about 19 percent, given the
|
||
following inputs:
|
||
Stock: $35.10
|
||
Strike: 35
|
||
Days to expiration: 44
|
||
Interest: 5.25 percent
|
||
No dividend paid during this period
|
||
Consequently, the vega is 0.048. What does the 0.048 vega tell Kim?
|
||
Given the preceding inputs, for each point the IV rises or falls, the option’s
|
||
value gains or loses about $0.05.
|
||
Some of the inputs, however, will change. Kim anticipates that Disney
|
||
will rise in price. She may be right or wrong. Either way, it is unlikely that
|
||
the stock will remain exactly at $35.10 to option expiration. The only
|
||
certainty is that time will pass.
|
||
Both price and time will change Kim’s vega exposure. Exhibit 4.5 shows
|
||
the changing vega of the 35 call as time and the underlying price change.
|
||
EXHIBIT 4.5 Disney 35 call price–time matrix–vega.
|
||
When comparing Exhibit 4.5 to Exhibit 4.3 , it’s easy to see that as the
|
||
time value of the option declines, so does Kim’s exposure to vega. As time
|
||
passes, vega gets smaller. And as the call becomes more in- or out-of-the-
|
||
money, vega gets smaller. Since she plans to hold the position for around
|
||
three weeks, she is not concerned about small fluctuations in IV in the
|
||
interim.
|
||
If indeed the rise in price that Kim anticipates comes to pass, vega
|
||
becomes even less of a concern. With 23 days to expiration and DIS at $37,
|
||
the call value is 2.21. The vega is $0.018. If IV decreases as the stock price
|
||
rises—a common occurrence—the adverse effect of vega will be minimal.
|
||
Even if IV declines by 5 points, to a historically low IV for DIS, the call
|
||
loses less than $0.10. That’s less than 5 percent of the new value of the
|
||
option.
|
||
If dividend policy changes or the interest rate changes, the value of Kim’s
|
||
call will be affected as well. Dividends are often fairly predictable.
|
||
However, a large unexpected dividend payment can have a significant
|
||
adverse impact on the value of the call. For example, if a surprise $3
|
||
dividend were announced, owning the stock would become greatly
|
||
preferable to owning the call. This preference would be reflected in the call
|
||
premium. This is a scenario that an experienced trader like Kim will realize
|
||
is a possibility, although not a probability. Although she knows it can
|
||
happen, she will not plan for such an event unless she believes it is likely to
|
||
happen. Possible reasons for such a belief could be rumors or the
|
||
company’s historically paying an irregular dividend.
|
||
Rho
|
||
For all intents and purposes, rho is of no concern to Kim. In recent years,
|
||
interest rate changes have not been a major issue for option traders. In the
|
||
Alan Greenspan years of Federal Reserve leadership, changes in the interest
|
||
rate were usually announced at the regularly scheduled Federal Open
|
||
Market Committee (FOMC) meetings, with but a few exceptions. Ben
|
||
Bernanke, likewise, changed interest rates fairly predictably, when he made
|
||
any rate changes at all. In these more stable periods, if there is no FOMC
|
||
meeting scheduled during the life of the call, it’s unlikely that rates will
|
||
change. Even if they do, the rho with 44 days to expiration is only 0.023.
|
||
This means that if rates change by a whole percentage point—which is four
|
||
times the most common incremental change—the call value will change by
|
||
a little more than $0.02. In this case, this is an acceptable risk. With 23 days
|
||
to expiration, the ATM 35 call has a rho of only 0.011.
|
||
Tweaking Greeks
|
||
With this position, some risks are of greater concern than others. Kim may
|
||
want more exposure to some greeks and less to others. What if she is
|
||
concerned that her forecasted price increase will take longer than three
|
||
weeks? She may want less exposure to theta. What if she is particularly
|
||
concerned about a decline in IV? She may want to decrease her vega.
|
||
Conversely, she may believe IV will rise and therefore want to increase her
|
||
vega.
|
||
Kim has many ways at her disposal to customize her greeks. All of her
|
||
alternatives come with trade-offs. She can buy more calls, increasing her
|
||
greek positions in exact proportion. She can buy or sell stock or options
|
||
against her call, creating a spread. The simplest way to alter her exposure to
|
||
option greeks is to choose a different call to buy. Instead of buying the ATM
|
||
call, Kim can buy a call with a different relationship to the current stock
|
||
price.
|
||
Long OTM Call
|
||
Kim can reduce her exposure to theta and vega by buying an OTM call. The
|
||
trade-off here is that she also reduces her immediate delta exposure.
|
||
Depending on how much Kim believes Disney will rally, this may or may
|
||
not be a viable trade-off. Imagine that instead of buying one Disney March
|
||
35 call, Kim buys one Disney March 37.50 call, for 0.20.
|
||
There are a few observations to be made about this alternative position.
|
||
First, the net premium, and therefore overall risk, is much lower, 0.20
|
||
instead of 1.10. From an expiration standpoint, the breakeven at expiration
|
||
is $37.70 (the strike price plus the call premium). Since Kim plans on
|
||
exiting the position after about three weeks, the exact break-even point at
|
||
the expiration of the contract is irrelevant. But the concept is the same: the
|
||
stock needs to rise significantly. Exhibit 4.6 shows how Kim’s concerns
|
||
translate into greeks.
|
||
EXHIBIT 4.6 Greeks for Disney 35 and 37.50 calls.
|
||
35 Call37.50 Call
|
||
Delta 0.57 0.185
|
||
Gamma0.1660.119
|
||
Theta −0.013−0.007
|
||
Vega 0.0480.032
|
||
Rho 0.0230.007
|
||
This table compares the ATM call with the OTM call. Kim can reduce her
|
||
theta to half that of the ATM call position by purchasing an OTM. This is
|
||
certainly a favorable difference. Her vega is lower with the 37.50 call, too.
|
||
This may or may not be a favorable difference. That depends on Kim’s
|
||
opinion of IV.
|
||
On the surface, the disparity in delta appears to be a highly unfavorable
|
||
trade-off. The delta of the 37.50 call is less than one third of the delta of the
|
||
35 call, and the whole motive for entering into this trade is to trade
|
||
direction! Although this strategy is very delta oriented, its core is more
|
||
focused on gamma and theta.
|
||
The gamma of the 37.50 call is about 72 percent that of the 35 call. But
|
||
the theta of the 37.50 call is about half that of the 35 call. Kim is improving
|
||
her gamma/theta relationship by buying the OTM, but with the call being so
|
||
far out-of-the-money and so inexpensive, the theta needs to be taken with a
|
||
grain of salt. It is ultimately gamma that will make or break this delta play.
|
||
The price of the option is 0.20—a rather low premium. In order for the
|
||
call to gain in value, delta has to go to work with help from gamma. At this
|
||
point, the delta is small, only 0.185. If Kim’s forecast is correct and there is
|
||
a big move upward, gamma will cause the delta to increase, and therefore
|
||
also the premium to increase exponentially. The call’s sensitivity to gamma,
|
||
however, is dynamic.
|
||
Exhibit 4.7 shows how the gamma of the 37.50 call changes as the stock
|
||
price moves over time. At any point in time, gamma is highest when the call
|
||
is ATM. However, so is theta. Kim wants to reap as much benefit from
|
||
gamma as possible while minimizing her exposure to theta. Ideally, she
|
||
wants Disney to rally through the strike price—through the high gamma
|
||
and back to the low theta. After three weeks pass, with 23 days until
|
||
expiration, if Disney is at $37 a share, the gamma almost doubles, to 0.237.
|
||
When the call is ATM, the delta increases at its fastest rate. As Disney rises
|
||
above the strike, the gamma figures in the table begin to decline.
|
||
EXHIBIT 4.7 Disney 37.50 call price–time matrix–gamma.
|
||
|
||
Gamma helps as the stock price declines, too. Exhibit 4.8 shows the effect
|
||
of time and gamma on the delta of the 37.50 call.
|
||
EXHIBIT 4.8 Disney 37.50 call price–time matrix–delta.
|
||
The effect of gamma is readily observable, as the delta at any point in
|
||
time is always higher at higher stock prices and lower at lower stock prices.
|
||
Kim benefits greatly when the delta grows from its initial level of 0.185 to
|
||
above 0.50—above the point of being at-the-money. If the stock moves
|
||
lower, gamma helps take away the pain of the price decline by decreasing
|
||
the delta.
|
||
While delta, gamma, and theta occupy Kim’s thoughts, it is ultimately
|
||
dollars and cents that matter. She needs to translate her study of the greeks
|
||
into cold, hard cash. Exhibit 4.9 shows the theoretical values of the 37.50
|
||
call.
|
||
EXHIBIT 4.9 Disney 37.50 call price–time matrix–value.
|
||
The sooner the price rise occurs, the better. It means less time for theta to
|
||
eat away profits. If Kim must hold the position for the entire three weeks,
|
||
she needs a good pop in the stock to make it worth her while. At a $37 share
|
||
price, the call is worth about 0.50, assuming all other market influences
|
||
remain constant. That’s about a 150 percent profit. At $38, Exhibit 4.9
|
||
reveals the call value to be 1.04. That’s a 420 percent profit.
|
||
On one hand, it’s hard for a trader like Kim not to get excited about the
|
||
prospect of making 420 percent on an 8 percent move in a stock. On the
|
||
other hand, Kim has to put things in perspective. When the position is
|
||
established, the call has a 0.185 delta. By the trader’s definition of delta,
|
||
that means the call is estimated to have about an 18.5 percent chance of
|
||
expiring in-the-money. More than four out of five times, this position will
|
||
be trading below the strike at expiration.
|
||
Although Kim is not likely to hold the position until expiration, this
|
||
observation tells her something: she’s starting in the hole. She is more likely
|
||
to lose than to win. She needs to be compensated well for her risk on the
|
||
winners to make up for the more prevalent losers.
|
||
Buying OTM calls can be considered more speculative than buying ITM
|
||
or ATM calls. Unlike what the at-expiration diagrams would lead one to
|
||
believe, OTM calls are not simply about direction. There’s a bit more to it.
|
||
They are really about gamma, time, and the magnitude of the stock’s move
|
||
(volatility). Long OTM calls require a big move in the right direction for
|
||
gamma to do its job.
|
||
Long ITM Call
|
||
Kim also has the alternative to buy an ITM call. Instead of the 35 or 37.50
|
||
call, she can buy the 32.50. The 32.50 call shares some of the advantages
|
||
the 37.50 call has over the 35 call, but its overall greek characteristics make
|
||
it a very different trade from the two previous alternatives. Exhibit 4.10
|
||
shows a comparison of the greeks of the three different calls.
|
||
EXHIBIT 4.10 Greeks for Disney 32.50, 35, and 37.50 calls.
|
||
Like the 37.50 call, the 32.50 has a lower gamma, theta, and vega than the
|
||
ATM 35-strike call. Because the call is ITM, it has a higher delta: 0.862. In
|
||
this example, Kim can buy the 32.50 call for 3. That’s 0.40 over parity (3 −
|
||
[35.10 − 32.50] = 0.40). There is not much time value, but more than the
|
||
37.50 call has. Thus, theta is of some concern. Ultimately, the ITMs have
|
||
0.40 of time value to lose compared with the 0.20 of the OTM calls. Vega is
|
||
also of some concern, but not as much as in the other alternatives because
|
||
the vega of the 32.50 is lower than the 35s or the 37.50s. Gamma doesn’t
|
||
help much as the stock rallies—it will get smaller as the stock price rises.
|
||
Gamma will, however, slow losses somewhat if the stock declines by
|
||
decreasing delta at an increasing rate.
|
||
In this case, the greek of greatest consequence is delta—it is a more
|
||
purely directional play than the other alternatives discussed. Exhibit 4.11
|
||
shows the matrix of the delta of the 32.50 call.
|
||
EXHIBIT 4.11 Disney 32.50 call price–time matrix–delta.
|
||
Because the call starts in-the-money and has a relatively low gamma, the
|
||
delta remains high even if Disney declines significantly. Gamma doesn’t
|
||
really kick in until the stock retreats enough to bring the call closer to being
|
||
at-the-money. At that point, the position will have suffered a big loss, and
|
||
the higher gamma is of little comfort.
|
||
Kim’s motivation for selecting the ITM call above the ATM and OTM
|
||
calls would be increased delta exposure. The 0.86 delta makes direction the
|
||
most important concern right out of the gate. Exhibit 4.12 shows the
|
||
theoretical values of the 32.50 call.
|
||
EXHIBIT 4.12 Disney 32.50 call price–time matrix–value.
|
||
Small directional moves contribute to significant leveraged gains or
|
||
losses. From share price $35 to $36, the call gains 0.90—from 2.91 to 3.81
|
||
—about a 30 percent gain. However, from $35 to $34, the call loses 0.80, or
|
||
27 percent. With only 0.40 of time value, the nondirectional greeks (theta,
|
||
gamma, and vega) are a secondary consideration.
|
||
If this were a deeper ITM call, the delta would start out even higher,
|
||
closer to 1.00, and the other relevant greeks would be closer to zero. The
|
||
deeper ITM a call, the more it acts like the stock and the less its option
|
||
characteristics (greeks) come into play.
|
||
Long ATM Put
|
||
The beauty of the free market is that two people can study all the available
|
||
information on the same stock and come up with completely different
|
||
outlooks. First of all, this provides for entertaining television on the
|
||
business-news channels when the network juxtaposes an outspoken bullish
|
||
analyst with an equally unreserved bearish analyst. But differing opinions
|
||
also make for a robust marketplace. Differing opinions are the oil that
|
||
greases the machine that is price discovery. From a market standpoint, it’s
|
||
what makes the world go round.
|
||
It is possible that there is another trader, Mick, in the market studying
|
||
Disney, who arrives at the conclusion that the stock is overpriced. Mick
|
||
believes the stock will decline in price over the next three weeks. He
|
||
decides to buy one Disney March 35 put at 0.80. In this example, March has
|
||
44 days to expiration.
|
||
Mick initiates this long put position to gain downside exposure, but along
|
||
with his bearish position comes option-specific risk and opportunity. Mick
|
||
is buying the same month and strike option as Kim did in the first example
|
||
of this chapter: the March 35 strike. Despite the different directional bias,
|
||
Mick’s position and Kim’s position share many similarities. Exhibit 4.13
|
||
offers a comparison of the greeks of the Disney March 35 call and the
|
||
Disney March 35 put.
|
||
EXHIBIT 4.13 Greeks for Disney 35 call and 35 put.
|
||
Call Put
|
||
Delta 0.57 −0.444
|
||
Gamma0.1660.174
|
||
Theta −0.013−0.009
|
||
Vega 0.0480.048
|
||
Rho 0.023−0.015
|
||
The first comparison to note is the contrasting deltas. The put delta is
|
||
negative, in contrast to the call delta. The absolute value of the put delta is
|
||
close to 1.00 minus the call delta. The put is just slightly OTM, so its delta
|
||
is just under 0.50, while that of the call is just over 0.50. The disparate, yet
|
||
related deltas represent the main difference between these two trades.
|
||
The difference between the gamma of the 35 put and that of the
|
||
corresponding call is fairly negligible: 0.174 versus 0.166, respectively. The
|
||
gamma of this ATM put will enter into the equation in much the same way
|
||
as the gamma of the ATM call. The put’s negative delta will become more
|
||
negative as the stock declines, drawing closer to −1.00. It will get less
|
||
negative as the stock price rises, drawing closer to zero. Gamma is
|
||
important here, because it helps the delta. Delta, however, still remains the
|
||
most important greek. Exhibit 4.14 illustrates how the 35 put delta changes
|
||
as time and price change.
|
||
EXHIBIT 4.14 Disney 35 put price–time matrix–delta.
|
||
Since this put is ATM, it starts out with a big enough delta to offer the
|
||
directional exposure Mick desires. The delta can change, but gamma
|
||
ensures that it always changes in Mick’s favor. Exhibit 4.15 shows how the
|
||
value of the 35 put changes with the stock price.
|
||
EXHIBIT 4.15 Disney 35 put price–time matrix–value.
|
||
Over time, a decline of only 10 percent in the stock yields high
|
||
percentage returns. This is due to the leveraged directional nature of this
|
||
trade—delta.
|
||
While the other greeks are not of primary concern, they must be
|
||
monitored. At the onset, the 0.80 premium is all time value and, therefore
|
||
subject to the influences of time decay and volatility. This is where trading
|
||
greeks comes into play.
|
||
Conventional trading wisdom says, “Cut your losses early, and let your
|
||
profits run.” When trading a stock, that advice is intellectually easy to
|
||
understand, although psychologically difficult to follow. Buyers of options,
|
||
especially ATM options, must follow this advice from the standpoint of
|
||
theta. Options are decaying assets. The time premium will be zero at
|
||
expiration. ATMs decay at an increasing nonlinear rate. Exiting a long
|
||
position before getting too close to expiration can cut losses caused by an
|
||
increasing theta. When to cut those losses, however, will differ from trade
|
||
to trade, situation to situation, and person to person.
|
||
When buying options, accepting some loss of premium due to time decay
|
||
should be part of the trader’s plan. It comes with the territory. In this
|
||
example, Mick is willing to accept about three weeks of erosion. Mick
|
||
needs to think about what his put will be worth, not just if the underlying
|
||
rises or falls but also if it doesn’t move at all. At the time the position is
|
||
established, the theta is 0.009, just under a penny. If Disney share price is
|
||
unchanged when three weeks pass, his theta will be higher. Exhibit 4.16
|
||
shows how thetas and theoretical values change over time if DIS stock
|
||
remains at $35.10.
|
||
EXHIBIT 4.16 Disney 35 put—thetas and theoretical values.
|
||
Mick needs to be concerned not only about what the theta is now but what
|
||
it will be when he plans on exiting the position. His plan is to exit the trade
|
||
in about three weeks, at which point the put theta will be −0.013. If he
|
||
amortizes his theta over this three-week period, he theoretically loses an
|
||
average of about 0.01 a day during this time if nothing else changes. The
|
||
average daily theta is calculated here by subtracting the value of the put at
|
||
23 days to expiration from its value when the trade was established to find
|
||
the loss of premium attributed to time decay, then dividing by the number
|
||
of days until expiration.
|
||
Since the theta doesn’t change much over the first three weeks, Mick can
|
||
eyeball the theta rather easily. As expiration approaches and theta begins to
|
||
grow more quickly, he’ll need to do the math.
|
||
At nine days to expiration, the theoretical value of Mick’s put is about
|
||
0.35, assuming all other variables are held constant. By that time, he will
|
||
have lost 0.45 (0.80 − 0.35) due to erosion over the 35-day period he held
|
||
the position if the stock hasn’t moved. Mick’s average daily theta during
|
||
that period is about 0.0129 (0.45 ÷ 35). The more time he holds the trade,
|
||
the greater a concern is theta. Mick must weigh his assessment of the
|
||
likelihood of the option’s gaining value from delta against the risk of
|
||
erosion. If he holds the trade for 35 days, he must make 0.0129 on average
|
||
per day from delta to offset theta losses. If the forecast is not realized within
|
||
the expected time frame or if the forecast changes, Mick needs to act fast to
|
||
curtail average daily theta losses.
|
||
Finding the Right Risk
|
||
Mick could lower the theta of his position by selecting a put with a greater
|
||
number of days to expiration. This alternative has its own set of trade-offs:
|
||
lower gamma and higher vega than the 44-day put. He could also select an
|
||
ITM put or an OTM put. Like Kim’s call alternatives, the OTM put would
|
||
have less exposure to time decay, lower vega, lower gamma, and a lower
|
||
delta. It would have a lower premium, too. It would require a bigger price
|
||
decline than the ATM put and would be more speculative.
|
||
The ITM put would also have lower theta, vega, and gamma, but it would
|
||
have a higher delta. It would take on more of the functionality of a short
|
||
stock position in much the same way that Kim’s ITM call alternative did for
|
||
a long stock position. In its very essence, however, an option trade, ITM or
|
||
otherwise, is still fundamentally different than a stock trade.
|
||
Stock has a 1.00 delta. The delta of a stock never changes, so it has zero
|
||
gamma. Stock is not subject to time decay and has no volatility component
|
||
to its pricing. Even though ITM options have deltas that approach 1.00 and
|
||
other greeks that are relatively low, they have two important differences
|
||
from an equity. The first is that the greeks of options are dynamic. The
|
||
second is the built-in leverage feature of options.
|
||
The relationship of an option’s strike price to the stock price can change
|
||
constantly. Options that are ITM now may be OTM tomorrow and vice
|
||
versa. Greeks that are not in play at the moment may be later. Even if there
|
||
is no time value in the option now because it is so far away-from-the-
|
||
money, there is the potential for time premium to become a component of
|
||
the option’s price if the stock moves closer to the strike price. Gamma,
|
||
theta, and vega always have the potential to come into play.
|
||
Since options are leveraged by nature, small moves in the stock can
|
||
provide big profits or big losses. Options can also curtail big losses if used
|
||
for hedging. Long option positions can reap triple-digit percentage gains
|
||
quickly with a favorable move in the underlying. Even though 100 percent
|
||
of the premium can be lost just as easily, one option contract will have far
|
||
less nominal exposure than a similar position in the stock.
|
||
It’s All About Volatility
|
||
What are Kim and Mick really trading? Volatility. The motivation for
|
||
buying an option as opposed to buying or shorting the stock is volatility. To
|
||
some degree, these options have exposure to both flavors of volatility—
|
||
implied volatility and historical volatility (HV). The positions in each of the
|
||
examples have positive vega. Their values are influenced, in part, by IV.
|
||
Over time, IV begins to lose its significance if the option is no longer close
|
||
to being at-the-money.
|
||
The main objective of each of these trades is to profit from the volatility
|
||
of the stock’s price movement, called future stock volatility or future
|
||
realized volatility. The strategies discussed in this chapter are contingent on
|
||
volatility being one directional. The bigger the move in the trader’s
|
||
forecasted direction the better. Volatility in the form of an adverse
|
||
directional move results in a decline in premium. The gamma in these long
|
||
option positions makes volatility in the right direction more beneficial and
|
||
volatility in the wrong direction less costly.
|
||
This phenomenon is hardly unique to the long call and the long put.
|
||
Although some basic strategies, such as the ones studied in this chapter,
|
||
depend on a particular direction, many don’t. Except for interest rate
|
||
strategies and perhaps some arbitrage strategies, all option trades are
|
||
volatility trades in one way or another. In general, option strategies can be
|
||
divided into two groups: volatility-buying strategies and volatility-selling
|
||
strategies. The following is a breakdown of common option strategies into
|
||
categories of volatility-buying strategies and volatility-selling strategies:
|
||
Volatility-Selling Strategies Volatility-Buying Strategies
|
||
Short Call, Short Put, Covered Call, Covered Put,
|
||
Bull Call Spread, Bear Call Spread, Bull Put
|
||
Spread, Bear Put Spread, Short Straddle, Short
|
||
Strangle, Guts, Ratio Call Spread, Calendar,
|
||
Butterfly, Iron Butterfly, Broken-Wing Butterfly,
|
||
Condor, Iron Condor, Diagonals, Double Diagonals,
|
||
Risk Reversals/Collars.
|
||
Long Call, Long Put, Bull Call Spread, Bear
|
||
Call Spread, Bull Put Spread, Bear Put Spread,
|
||
Long Straddle, Long Strangle, Guts, Back
|
||
Spread, Calendar, Butterfly, Iron Butterfly,
|
||
Broken-Wing Butterfly, Condor, Iron Condor,
|
||
Diagonals, Double Diagonals, Risk
|
||
Reversals/Collars.
|
||
Long option strategies appear in the volatility-buying group because they
|
||
have positive gamma and positive vega. Short option strategies appear in
|
||
the volatility-selling group because of negative gamma and vega. There are
|
||
some strategies that appear in both groups—for example, the
|
||
butterfly/condor family, which is typically associated with income
|
||
generation. These particular volatility strategies are commonly instituted as
|
||
volatility-selling strategies. However, depending on whether the position is
|
||
bought or sold and where the stock price is in relation to the strike prices,
|
||
the position could fall into either group. Some strategies, like the vertical
|
||
spread family—bull and bear call and put spreads—and risk reversal/collar
|
||
spreads naturally fall into either category, depending on where the stock is
|
||
in relation to the strikes. The calendar spread family is unique in that it can
|
||
have characteristics of each group at the same time.
|
||
Direction Neutral, Direction Biased, and
|
||
Direction Indifferent
|
||
As typically traded, volatility-selling option strategies are direction neutral.
|
||
This means that the position has the greatest results if the underlying price
|
||
remains in a range—that is, neutral. Although some option-selling strategies
|
||
—for example, a naked put—may have a positive or negative delta in the
|
||
short term, profit potential is decidedly limited. This means that if traders
|
||
are expecting a big move, they are typically better off with option-buying
|
||
strategies.
|
||
Option-buying strategies can be either direction biased or direction
|
||
indifferent. Direction-biased strategies have been shown throughout this
|
||
chapter. They are delta trades. Direction-indifferent strategies are those that
|
||
benefit from increased volatility in the underlying but where the direction of
|
||
the move is irrelevant to the profitability of the trade. Movement in either
|
||
direction creates a winner.
|
||
Are You a Buyer or a Seller?
|
||
The question is: which is better, selling volatility or buying volatility? I
|
||
have attended option seminars with instructors (many of whom I regard
|
||
with great respect) teaching that volatility-selling strategies, or income-
|
||
generating strategies, are superior to buying options. I also know option
|
||
gurus that tout the superiority of buying options. The answer to the question
|
||
of which is better is simple: it’s all a matter of personal preference.
|
||
When I began trading on the floor of Chicago Board Options Exchange
|
||
(CBOE) in the 1990s, I quickly became aware of a dichotomy among my
|
||
market-making peers. Those making markets on the floor of the exchange at
|
||
that time were divided into two groups: teenie buyers and teenie sellers.
|
||
Teenie Buyers
|
||
Before options traded in decimals (dollars and cents) like they do today, the
|
||
lowest price increment in which an option could be traded was one
|
||
sixteenth of a dollar—a teenie . Teenie buyers were market makers who
|
||
would buy back OTM options at one sixteenth to eliminate short positions.
|
||
They would sometimes even initiate long OTM option positions at a teenie,
|
||
too. The focus of the teenie-buyer school of thought was the fact that long
|
||
options have unlimited reward, while short options have unlimited risk. An
|
||
option purchased so far OTM that it was offered at one sixteenth is unlikely
|
||
to end up profitable, but it’s an inexpensive lottery ticket. At worst, the
|
||
trader can only lose a teenie. Teenie buyers felt being short OTM options
|
||
that could be closed by paying a sixteenth was an unreasonable risk.
|
||
Teenie Sellers
|
||
Teenie sellers, however, focused on the fact that options offered at one
|
||
sixteenth were far enough OTM that they were very likely to expire
|
||
worthless. This appears to be free money, unless the unexpected occurs, in
|
||
which case potential losses can be unlimited. Teenie sellers would routinely
|
||
save themselves $6.25 (one sixteenth of a dollar per contract representing
|
||
100 shares) by selling their long OTMs at a teenie to close the position.
|
||
They sometimes would even initiate short OTM contracts at one sixteenth.
|
||
These long-option or short-option biases hold for other types of strategies
|
||
as well. Volatility-selling positions, such as the iron condor, can be
|
||
constructed to have limited risk. The paradigm for these strategies is they
|
||
tend to produce winners more often than not. But when the position loses,
|
||
the trader loses more than he would stand to profit if the trade worked out
|
||
favorably.
|
||
Herein lies the issue of preference. Long-option traders would rather trade
|
||
Babe Ruth–style. For years, Babe Ruth was the record holder for the most
|
||
home runs. At the same time, he was also the record holder for the most
|
||
strikeouts. The born fighters that are option buyers accept the fact that they
|
||
will have more strikeouts, possibly many more strikeouts, than winning
|
||
trades. But the strategy dictates that the profit on one winner more than
|
||
makes up for the string of small losers.
|
||
Short-option traders, conversely, like to have everything cool and
|
||
copacetic. They like the warm and fuzzy feeling they get from the fact that
|
||
month after month they tend to generate winners. The occasional loser that
|
||
nullifies a few months of profits is all part of the game.
|
||
Options and the Fair Game
|
||
There may be a statistical advantage to buying stock as opposed to shorting
|
||
stock, because the market has historically had a positive annualized return
|
||
over the long run. A statistical advantage to being either an option buyer or
|
||
an option seller, however, should not exist in the long run, because the
|
||
option market prices IV. Assuming an overall efficient market for pricing
|
||
volatility into options, there should be no statistical advantage to
|
||
systematically buying or selling options. 1
|
||
Consider a game consisting of one six-sided die. Each time a one, two, or
|
||
three is rolled, the house pays the player $1. Each time a four, five, or six is
|
||
rolled, the house pays zero. What is the most a player would be willing to
|
||
pay to play this game? If the player paid nothing, the house would be at a
|
||
tremendous disadvantage, paying $1 50 percent of the time and nothing the
|
||
other 50 percent of the time. This would not be a fair game from the house’s
|
||
perspective, as it would collect no money. If the player paid $1, the player
|
||
would get his dollar back when one, two, or three came up. Otherwise, he
|
||
would lose his dollar. This is not a fair game from the player’s perspective.
|
||
The chances of winning this game are 3 out of 6, or 50–50. If this game
|
||
were played thousands of times, one would expect to receive $1 half the
|
||
time and receive nothing the other half of the time. The average return per
|
||
roll one would expect to receive would be $0.50, that’s ($1 × 50 percent +
|
||
$0 × 50 percent). This becomes a fair game with an entrance fee of $0.50.
|
||
Now imagine a similar game in which a six-sided die is rolled. This time
|
||
if a one is rolled, the house pays $1. If any other number is rolled, the house
|
||
pays nothing. What is a fair price to play this game? The same logic and the
|
||
same math apply. There is a
|
||
percent chance of a one coming up and the
|
||
player receiving $1. And there is a
|
||
percent chance of each of the other
|
||
five numbers being rolled and the player receiving nothing. Mathematically,
|
||
this translates to:
|
||
percent
|
||
percent). Fair value for a
|
||
chance to play this game is about $0.1667 per roll.
|
||
The fair game concept applies to option prices as well. The price of the
|
||
game, or in this case the price of the option, is determined by the market in
|
||
the form of IV. The odds are based on the market’s expectations of future
|
||
volatility. If buying options offered a superior payout based on the odds of
|
||
success, the market would put upward pressure on prices until this arbitrage
|
||
opportunity ceased to exist. It’s the same for selling volatility. If selling
|
||
were a fundamentally better strategy, the market would depress option
|
||
prices until selling options no longer produced a way to beat the odds. The
|
||
options market will always equalize imbalances.
|
||
Note
|
||
1 . This is not to say that unique individual opportunities do not exist for
|
||
overpriced or underpriced options, only that options are not overpriced or
|
||
underpriced in general. Thus, neither an option-selling nor option-buying
|
||
methodology should provide an advantage.
|
||
CHAPTER 5
|
||
An Introduction to Volatility-Selling Strategies
|
||
Along with death and taxes, there is one other fact of life we can all count
|
||
on: the time value of all options ultimately going to zero. What an alluring
|
||
concept! In a business where expected profits can be thwarted by an
|
||
unexpected turn of events, this is one certainty traders can count on. Like all
|
||
certainties in the financial world, there is a way to profit from this fact, but
|
||
it’s not as easy as it sounds. Alas, the potential for profit only exists when
|
||
there is risk of loss.
|
||
In order to profit from eroding option premiums, traders must implement
|
||
option-selling strategies, also known as volatility-selling strategies. These
|
||
strategies have their own set of inherent risks. Selling volatility means
|
||
having negative vega—the risk of implied volatility rising. It also means
|
||
having negative gamma—the risk of the underlying being too volatile. This
|
||
is the nature of selling volatility. The option-selling trader does not want the
|
||
underlying stock to move—that is, the trader wants the stock to be less
|
||
volatile. That is the risk.
|
||
Profit Potential
|
||
Profit for the volatility seller is realized in a roundabout sort of way. The
|
||
reward for low volatility is achieved through time decay. These strategies
|
||
have positive theta. Just as the volatility-buying strategies covered in
|
||
Chapter 4 had time working against them, volatility-selling strategies have
|
||
time working in their favor. The trader is effectively paid to assume the risk
|
||
of movement.
|
||
Gamma-Theta Relationship
|
||
There exists a trade-off between gamma and theta. Long options have
|
||
positive gamma and negative theta. Short options have negative gamma and
|
||
positive theta. Positions with greater gamma, whether positive or negative,
|
||
tend to have greater theta values, negative or positive. Likewise, lower
|
||
absolute values for gamma tend to go hand in hand with lower absolute
|
||
values for theta. The gamma-theta relationship is the most important
|
||
consideration with many types of strategies. Gamma-theta is often the
|
||
measurement with the greatest influence on the bottom line.
|
||
Greeks and Income Generation
|
||
With volatility-selling strategies (sometimes called income-generating
|
||
strategies), greeks are often overlooked. Traders simply dismiss greeks as
|
||
unimportant to this kind of trade. There is some logic behind this reasoning.
|
||
Time decay provides the profit opportunity. In order to let all of time
|
||
premium erode, the position must be held until expiration. Interim changes
|
||
in implied volatility are irrelevant if the position is held to term. The
|
||
gamma-theta loses some significance if the position is held until expiration,
|
||
too. The position has either passed the break-even point on the at-expiration
|
||
diagram, or it has not. Incremental daily time decay–related gains are not
|
||
the ultimate goal. The trader is looking for all the time premium, not
|
||
portions of it.
|
||
So why do greeks matter to volatility sellers? Greeks allow traders to be
|
||
flexible. Consider short-term-momentum stock traders. The traders buy a
|
||
stock because they believe it will rise over the next month. After one week,
|
||
if unexpected bearish news is announced causing the stock to break through
|
||
its support lines, the traders have a decision to make. Short-term speculative
|
||
traders very often choose to cut their losses and exit the position early rather
|
||
than risk a larger loss hoping for a recovery.
|
||
Volatility-selling option traders are often faced with the same dilemma. If
|
||
the underlying stays in line with the traders’ forecast, there is little to worry
|
||
about. But if the environment changes, the traders have to react. Knowing
|
||
the greeks for a position can help traders make better decisions if they plan
|
||
to close the position before expiration.
|
||
Naked Call
|
||
A naked call is when a trader shorts a call without having stock or other
|
||
options to cover or protect it. Since the call is uncovered, it is one of the
|
||
riskier trades a trader can make. Recall the at-expiration diagram for the
|
||
naked call from Chapter 1, Exhibit 1.3 : Naked TGT Call. Theoretically,
|
||
there is limited reward and unlimited risk. Yet there are times when
|
||
experienced traders will justify making such a trade. When a stock has been
|
||
trading in a range and is expected to continue doing so, traders may wait
|
||
until it is near the top of the channel, where there is resistance, and then
|
||
short a call.
|
||
For example, a trader, Brendan, has been studying a chart of Johnson &
|
||
Johnson (JNJ). Brendan notices that for a few months the stock has trading
|
||
been in a channel between $60 and $65. As he observes Johnson & Johnson
|
||
beginning to approach the resistance level of $65 again, he considers selling
|
||
a call to speculate on the stock not rising above $65. Before selling the call,
|
||
Brendan consults other technical analysis tools, like ADX/DMI, to confirm
|
||
that there is no trend present. ADX/DMI is used by some traders as a filter
|
||
to determine the strength of a trend and whether the stock is overbought or
|
||
oversold. In this case, the indicator shows no strong trend present. Brendan
|
||
then performs due diligence. He studies the news. He looks for anything
|
||
specific that could cause the stock to rally. Is the stock a takeover target?
|
||
Brendan finds nothing. He then does earnings research to find out when
|
||
they will be announced, which is not for almost two more months.
|
||
Next, Brendan pulls up an option chain on his computer. He finds that
|
||
with the stock trading around $64 per share, the market for the November
|
||
65 call (expiring in four weeks) is 0.66 bid at 0.68 offer. Brendan considers
|
||
when Johnson & Johnson’s earnings report falls. Although recent earnings
|
||
have seldom been a major concern for Johnson & Johnson, he certainly
|
||
wants to sell an option expiring before the next earnings report. The
|
||
November fits the mold. Brendan sells ten of the November 65 calls at the
|
||
bid price of 0.66.
|
||
Brendan has a rather straightforward goal. He hopes to see Johnson &
|
||
Johnson shares remain below $65 between now and expiration. If he is
|
||
right, he stands to make $660. If he is wrong? Exhibit 5.1 shows how
|
||
Brendan’s calls hold up if they are held until expiration.
|
||
EXHIBIT 5.1 Naked Johnson & Johnson call at expiration.
|
||
Considering the risk/reward of this trade, Brendan is rightfully concerned
|
||
about a big upward move. If the stock begins to rally, he must be prepared
|
||
to act fast. Brendan must have an idea in advance of what his pain threshold
|
||
is. In other words, at what price will he buy back his calls and take a loss if
|
||
Johnson & Johnson moves adversely?
|
||
He decides he will buy all 10 of his calls back at 1.10 per contract if the
|
||
trade goes against him. (1.10 is an arbitrary price used for illustrative
|
||
purposes. The actual price will vary, based on the situation and the risk
|
||
tolerance of the trader. More on when to take profits and losses is discussed
|
||
in future chapters.) He may choose to enter a good-till-canceled (GTC)
|
||
stop-loss order to buy back his calls. Or he may choose to monitor the stock
|
||
and enter the order when he sees the calls offered at 1.10—a mental stop
|
||
order. What Brendan needs to know is: How far can the stock price advance
|
||
before the calls are at 1.10?
|
||
Brendan needs to examine the greeks of this trade to help answer this
|
||
question. Exhibit 5.2 shows the hypothetical greeks for the position in this
|
||
example.
|
||
EXHIBIT 5.2 Greeks for short Johnson & Johnson 65 call (per contract).
|
||
Delta −0.34
|
||
Gamma−0.15
|
||
Theta 0.02
|
||
Vega −0.07
|
||
The short call has a negative delta. It also has negative gamma and vega,
|
||
but it has positive time decay (theta). As Johnson & Johnson ticks higher,
|
||
the delta increases the nominal value of the call. Although this is not a
|
||
directional trade per se, delta is a crucial element. It will have a big impact
|
||
on Brendan’s expectations as to how high the stock can rise before he must
|
||
take his loss.
|
||
First, Brendan considers how much the option price can move before he
|
||
covers. The market now is 0.66 bid at 0.68 offer. To buy back his calls at
|
||
1.10, they must be offered at 1.10. The difference between the offer now
|
||
and the offer price at which Brendan will cover is 0.42 (that’s 1.10 − 0.68).
|
||
Brendan can use delta to convert the change in the ask prices into a stock
|
||
price change. To do so, Brendan divides the change in the option price by
|
||
the delta.
|
||
The −0.34 delta indicates that if JNJ rises $1.24, the calls should be
|
||
offered at 1.10.
|
||
Brendan takes note that the bid-ask spreads are typically 0.01 to 0.03
|
||
wide in near-term Johnson & Johnson options trading under 1.00. This is
|
||
not necessarily the case in other option classes. Less liquid names have
|
||
wider spreads. If the spreads were wider, Brendan would have more
|
||
slippage. Slippage is the difference between the assumed trade price and the
|
||
actual price of the fill as a product of the bid-ask spread. It’s the difference
|
||
between theory and reality. If the bid-ask spread had a typical width of, say,
|
||
0.70, the market would be something more like 0.40 bid at 1.10 offer. In
|
||
this case, if the stock moved even a few cents higher, Brendan could not
|
||
buy his calls back at his targeted exit price of 1.10. The tighter markets
|
||
provide lower transaction costs in the form of lower slippage. Therefore,
|
||
there is more leeway if the stock moves adversely when there are tighter
|
||
bid-ask option spreads.
|
||
But just looking at delta only tells a part of the story. In reality, the delta
|
||
does not remain constant during the price rise in Johnson & Johnson but
|
||
instead becomes more negative. Initially, the delta is −0.34 and the gamma
|
||
is −0.15. After a rise in the stock price, the delta will be more negative by
|
||
the amount of the gamma. To account for the entire effect of direction,
|
||
Brendan needs to take both delta and gamma into account. He needs to
|
||
estimate the average delta based on gamma during the stock price move.
|
||
The formula for the change in stock price is
|
||
Taking into account the effect of gamma as well as delta, Johnson &
|
||
Johnson needs to rise only $1.01, in order for Brendan’s calls to be offered
|
||
at his stop-loss price of 1.10.
|
||
While having a predefined price point to cover in the event the underlying
|
||
rises is important, sometimes traders need to think on their feet. If material
|
||
news is announced that changes the fundamental outlook for the stock,
|
||
Brendan will have to adjust his plan. If the news leads Brendan to become
|
||
bullish on the stock, he should exit the trade at once, taking a small loss
|
||
now instead of the bigger loss he would expect later. If the trader is
|
||
uncertain as to whether to hold or close the position, the Would I Do It
|
||
Now? rule is a useful rule of thumb.
|
||
Would I Do It Now? Rule
|
||
To follow this rule, ask yourself, “If I did not already have this position,
|
||
would I do it now? Would I establish the position at the current market
|
||
prices, given the current market scenario?” If the answer is no, then the
|
||
solution is simple: Exit the trade.
|
||
For example, if after one week material news is released and Johnson &
|
||
Johnson is trading higher, at $64.50 per share, and the November 65 call is
|
||
trading at 0.75, Brendan must ask himself, based on the price of the stock
|
||
and all known information, “If I were not already short the calls, would I
|
||
short them now at the current price of 0.75, with the stock trading at
|
||
$64.50?”
|
||
Brendan’s opinion of the stock is paramount in this decision. If, for
|
||
example, based on the news that was announced he is now bullish, he
|
||
would likely not want to sell the calls at 0.75—he only gets $0.09 more in
|
||
option premium and the stock is 0.50 closer to the strike. If, however, he is
|
||
not bullish, there is more to consider.
|
||
Theta can be of great use in decision making in this situation. As the
|
||
number of days until expiration decreases and the stock approaches $65
|
||
(making the option more at-the-money), Brendan’s theta grows more
|
||
positive. Exhibit 5.3 shows the theta of this trade as the underlying rises
|
||
over time.
|
||
EXHIBIT 5.3 Theta of Johnson & Johnson.
|
||
When the position is first established, positive theta comforts Brendan by
|
||
showing that with each passing day he gets a little closer to his goal—to
|
||
have the 65 calls expire out-of-the-money (OTM) and reap a profit of the
|
||
entire 66-cent premium. Theta becomes truly useful if the position begins to
|
||
move against him. As Johnson & Johnson rises, the trade gets more
|
||
precarious. His negative delta increases. His negative gamma increases. His
|
||
goal becomes more out of reach. In conjunction with delta and gamma,
|
||
theta helps Brendan decide whether the risk is worth the reward.
|
||
In the new scenario, with the stock at $64.50, Brendan would collect $18
|
||
a day (1.80 × 10 contracts). Is the risk of loss in the short run worth earning
|
||
$18 a day? With Johnson & Johnson at $64.50, would Brendan now short
|
||
10 calls at 0.75 to collect $18 a day, knowing that each day may bring a
|
||
continued move higher in the stock? The answer to this question depends on
|
||
Brendan’s assessment of the risk of the underlying continuing its ascent. As
|
||
time passes, if the stock remains closer to the strike, the daily theta rises,
|
||
providing more reward. Brendan must consider that as theta—the reward—
|
||
rises, so does gamma: a risk factor.
|
||
A small but noteworthy risk is that implied volatility could rise. The
|
||
negative vega of this position would, then, adversely affect the profitability
|
||
of this trade. It will make Brendan’s 1.10 cover-point approach faster
|
||
because it makes the option more expensive. Vega is likely to be of less
|
||
consequence because it would ultimately take the stock’s rising though the
|
||
strike price for the trade to be a loser at expiration.
|
||
Short Naked Puts
|
||
Another trader, Stacie, has also been studying Johnson & Johnson. Stacie
|
||
believes Johnson & Johnson is on its way to test the $65 resistance level yet
|
||
again. She believes it may even break through $65 this time, based on
|
||
strong fundamentals. Stacie decides to sell naked puts. A naked put is a
|
||
short put that is not sold in conjunction with stock or another option.
|
||
With the stock around $64, the market for the November 65 put is 1.75
|
||
bid at 1.80. Stacie likes the fact that the 65 puts are slightly in-the-money
|
||
(ITM) and thus have a higher delta. If her price rise comes sooner than
|
||
expected, the high delta may allow her to take a profit early. Stacie sells 10
|
||
puts at 1.75.
|
||
In the best-case scenario, Stacie retains the entire 1.75. For that to happen,
|
||
she will need to hold this position until expiration and the stock will have to
|
||
rise to be trading above the 65 strike. Logically, Stacie will want to do an
|
||
at-expiration analysis. Exhibit 5.4 shows Stacie’s naked put trade if she
|
||
holds it until expiration.
|
||
EXHIBIT 5.4 Naked Johnson & Johnson put at expiration.
|
||
While harvesting the entire premium as a profit sounds attractive, if
|
||
Stacie can take the bulk of her profit early, she’ll be happy to close the
|
||
position and eliminate her risk—nobody ever went broke taking a profit.
|
||
Furthermore, she realizes that her outlook may be wrong: Johnson &
|
||
Johnson may decline. She may have to close the position early—maybe for
|
||
a profit, maybe for a loss. Stacie also needs to study her greeks. Exhibit 5.5
|
||
shows the greeks for this trade.
|
||
EXHIBIT 5.5 Greeks for short Johnson & Johnson 65 put (per contract).
|
||
Delta 0.65
|
||
Gamma−0.15
|
||
Theta 0.02
|
||
Vega −0.07
|
||
The first item to note is the delta. This position has a directional bias. This
|
||
bias can work for or against her. With a positive 0.65 delta per contract, this
|
||
position has a directional sensitivity equivalent to being long around 650
|
||
shares of the stock. That’s the delta × 100 shares × 10 contracts.
|
||
Stacie’s trade is not just a bullish version of Brendan’s. Partly because of
|
||
the size of the delta, it’s different—specific directional bias aside. First, she
|
||
will handle her trade differently if it is profitable.
|
||
For example, if over the next week or so Johnson & Johnson rises $1,
|
||
positive delta and negative gamma will have a net favorable effect on
|
||
Stacie’s profitability. Theta is small in comparison and won’t have too much
|
||
of an effect. Delta/gamma will account for a decrease in the put’s
|
||
theoretical value of about $0.73. That’s the estimated average delta times
|
||
the stock move, or [0.65 + (–0.15/2)] × 1.00.
|
||
Stacie’s actual profit would likely be less than 0.73 because of the bid-ask
|
||
spread. Stacie must account for the fact that the bid-ask is 0.05 wide (1.75–
|
||
1.80). Because Stacie would buy to close this position, she should consider
|
||
the 0.73 price change relative to the 1.80 offer, not the 1.75 trade price—
|
||
that is, she factors in a nickel of slippage. Thus, she calculates, that the puts
|
||
will be offered at 1.07 (that’s 1.80 − 0.73) when the stock is at $65. That is
|
||
a gain of $0.68.
|
||
In this scenario, Stacie should consider the Would I Do It Now? rule to
|
||
guide her decision as to whether to take her profit early or hold the position
|
||
until expiration. Is she happy being short ten 65 puts at 1.07 with Johnson
|
||
& Johnson at $65? The premium is lower now. The anticipated move has
|
||
already occurred, and she still has 28 days left in the option that could allow
|
||
for the move to reverse itself. If she didn’t have the trade on now, would she
|
||
sell ten 65 puts at 1.07 with Johnson & Johnson at $65? Based on her
|
||
original intention, unless she believes strongly now that a breakout through
|
||
$65 with follow-through momentum is about to take place, she will likely
|
||
take the money and run.
|
||
Stacie also must handle this trade differently from Brendan in the event
|
||
that the trade is a loser. Her trade has a higher delta. An adverse move in the
|
||
underlying would affect Stacie’s trade more than it would Brendan’s. If
|
||
Johnson & Johnson declines, she must be conscious in advance of where
|
||
she will cover.
|
||
Stacie considers both how much she is willing to lose and what potential
|
||
stock-price action will cause her to change her forecast. She consults a
|
||
stock chart of Johnson & Johnson. In this example, we’ll assume there is
|
||
some resistance developing around $64 in the short term. If this resistance
|
||
level holds, the trade becomes less attractive. The at-expiration breakeven is
|
||
$63.25, so the trade can still be a winner if Johnson & Johnson retreats. But
|
||
Stacie is looking for the stock to approach $65. She will no longer like the
|
||
risk/reward of this trade if it looks like that price rise won’t occur. She
|
||
makes the decision that if Johnson & Johnson bounces off the $64 level
|
||
over the next couple weeks, she will exit the position for fear that her
|
||
outlook is wrong. If Johnson & Johnson drifts above $64, however, she will
|
||
ride the trade out.
|
||
In this example, Stacie is willing to lose 1.00 per contract. Without taking
|
||
into account theta or vega, that 1.00 loss in the option should occur at a
|
||
stock price of about $63.28. Theta is somewhat relevant here. It helps
|
||
Stacie’s potential for profit as time passes. As time passes and as the stock
|
||
rises, so will theta, helping her even more. If the stock moves lower (against
|
||
her) theta helps ease the pain somewhat, but the further in-the-money the
|
||
put, the lower the theta.
|
||
Vega can be important here for two reasons: first, because of how implied
|
||
volatility tends to change with market direction, and second, because it can
|
||
be read as an indication of the market’s expectations.
|
||
The Double Whammy
|
||
With the stock around $64, there is a negative vega of about seven cents. As
|
||
the stock moves lower, away from the strike, the vega gets a bit smaller.
|
||
However, the market conditions that would lead to a decline in the price of
|
||
Johnson & Johnson would likely cause implied volatility (IV) to rise. If the
|
||
stock drops, Stacie would have two things working against her—delta and
|
||
vega—a double whammy. Stacie needs to watch her vega. Exhibit 5.6
|
||
shows the vega of Stacie’s put as it changes with time and direction.
|
||
EXHIBIT 5.6 Johnson & Johnson 65 put vega.
|
||
If after one week passes Johnson & Johnson gaps lower to, say, $63.00 a
|
||
share, the vega will be 0.043 per contract. If IV subsequently rises 5 points
|
||
as a result of the stock falling, vega will make Stacie’s puts theoretically
|
||
worth 21.5 cents more per contract. She will lose $215 on vega (that’s 0.043
|
||
vega × 5 volatility points × 10 contracts) plus the adverse delta/gamma
|
||
move.
|
||
A gap opening will cause her to miss the opportunity to stop herself out at
|
||
her target price entirely. Even if the stock drifts lower, her targeted stop-loss
|
||
price will likely come sooner than expected, as the option price will likely
|
||
increase both by delta/gamma and vega resulting from rising volatility. This
|
||
can cause her to have to cover sooner, which leaves less room for error.
|
||
With this trade, increases in IV due to market direction can make it feel as if
|
||
the delta is greater than it actually is as the market declines. Conversely, IV
|
||
softening makes it feel as if the delta is smaller than it is as the market rises.
|
||
The second reason IV has importance for this trade (as for most other
|
||
strategies) is that it can give some indication of how much the market thinks
|
||
the stock can move. If IV is higher than normal, the market perceives there
|
||
to be more risk than usual of future volatility. The question remains: Is the
|
||
higher premium worth the risk?
|
||
The answer to this question is subjective. Part of the answer is based on
|
||
Stacie’s assessment of future volatility. Is the market right? The other part is
|
||
based on Stacie’s risk tolerance. Is she willing to endure the greater price
|
||
swings associated with the potentially higher volatility? This can mean
|
||
getting whipsawed, which is exiting a position after reaching a stop-loss
|
||
point only to see the market reverse itself. The would-be profitable trade is
|
||
closed for a loss. Higher volatility can also mean a higher likelihood of
|
||
getting assigned and acquiring an unwanted long stock position.
|
||
Cash-Secured Puts
|
||
There are some situations where higher implied volatility may be a
|
||
beneficial trade-off. What if Stacie’s motivation for shorting puts was
|
||
different? What if she would like to own the stock, just not at the current
|
||
market price? Stacie can sell ten 65 puts at 1.75 and deposit $63,250 in her
|
||
trading account to secure the purchase of 1,000 shares of Johnson &
|
||
Johnson if she gets assigned. The $63,250 is the $65 per share she will pay
|
||
for the stock if she gets assigned, minus the 1.75 premium she received for
|
||
the put × $100 × 10 contracts. Because the cash required to potentially
|
||
purchase the stock is secured by cash sitting ready in the account, this is
|
||
called a cash-secured put.
|
||
Her effective purchase price if assigned is $63.25—the same as her
|
||
breakeven at expiration. The idea with this trade is that if Johnson &
|
||
Johnson is anywhere under $65 per share at expiration, she will buy the
|
||
stock effectively at $63.25. If assigned, the time premium of the put allows
|
||
her to buy the stock at a discount compared with where it is priced when the
|
||
trade is established, $64. The higher the time premium—or the higher the
|
||
implied volatility—the bigger the discount.
|
||
This discount, however, is contingent on the stock not moving too much.
|
||
If it is above $65 at expiration she won’t get assigned and therefore can
|
||
only profit a maximum of 1.75 per contract. If the stock is below $63.25 at
|
||
expiration, the time premium no longer represents a discount, in fact, the
|
||
trade becomes a loser. In a way, Stacie is still selling volatility.
|
||
Covered Call
|
||
The problem with selling a naked call is that it has unlimited exposure to
|
||
upside risk. Because of this, many traders simply avoid trading naked calls.
|
||
A more common, and some would argue safer, method of selling calls is to
|
||
sell them covered.
|
||
A covered call is when calls are sold and stock is purchased on a share-
|
||
for-share basis to cover the unlimited upside risk of the call. For each call
|
||
that is sold, 100 shares of the underlying security are bought. Because of the
|
||
addition of stock to this strategy, covered calls are traded with a different
|
||
motivation than naked calls.
|
||
There are clearly many similarities between these two strategies. The
|
||
main goal for both is to harvest the premium of the call. The theta for the
|
||
call is the same with or without the stock component. The gamma and vega
|
||
for the two strategies are the same as well. The only difference is the stock.
|
||
When stock is added to an option position, the net delta of the position is
|
||
the only thing affected. Stock has a delta of one, and all its other greeks are
|
||
zero.
|
||
The pivotal point for both positions is the strike price. That’s the point the
|
||
trader wants the stock to be above or below at expiration. With the naked
|
||
call, the maximum payout is reaped if the stock is below the strike at
|
||
expiration, and there is unlimited risk above the strike. With the covered
|
||
call, the maximum payout is reaped if the stock is above the strike at
|
||
expiration. If the stock is below the strike at expiration, the risk is
|
||
substantial—the stock can potentially go to zero.
|
||
Putting It on
|
||
There are a few important considerations with the covered call, both when
|
||
putting on, or entering, the position and when taking off, or exiting, the
|
||
trade. The risk/reward implications of implied volatility are important in the
|
||
trade-planning process. Do I want to get paid more to assume more
|
||
potential risk? More speculative traders like the higher premiums. More
|
||
conservative (investment-oriented) covered-call sellers like the low implied
|
||
risk of low-IV calls. Ultimately, a main focus of a covered call is the option
|
||
premium. How fast can it go to zero without the movement hurting me? To
|
||
determine this, the trader must study both theta and delta.
|
||
The first step in the process is determining which month and strike call to
|
||
sell. In this example, Harley-Davidson Motor Company (HOG) is trading at
|
||
about $69 per share. A trader, Bill, is neutral to slightly bullish on Harley-
|
||
Davidson over the next three months. Exhibit 5.7 shows a selection of
|
||
available call options for Harley-Davidson with corresponding deltas and
|
||
thetas.
|
||
EXHIBIT 5.7 Harley-Davidson calls.
|
||
In this example, the May 70 calls have 85 days until expiration and are
|
||
2.80 bid. If Harley-Davidson remained at $69 until May expiration, the 2.80
|
||
premium would represent a 4 percent profit over this 85-day period (2.80 ÷
|
||
69). That’s an annualized return of about 17 percent ([0.04 / 85)] × 365).
|
||
Bill considers his alternatives. He can sell the April (57-day) 70 calls at
|
||
2.20 or the March (22-day) 70 calls at 0.85. Since there is a different
|
||
number of days until expiration, Bill needs to compare the trades on an
|
||
apples-to-apples basis. For this, he will look at theta and implied volatility.
|
||
Presumably, the March call has a theta advantage over the longer-term
|
||
choices. The March 70 has a theta of 0.032, while the April 70’s theta is
|
||
0.026 and the May 70’s is 0.022. Based on his assessment of theta, Bill
|
||
would have the inclination to sell the March. If he wants exposure for 90
|
||
days, when the March 70 call expires, he can roll into the April 70 call and
|
||
then the May 70 call (more on this in subsequent chapters). This way Bill
|
||
can continue to capitalize on the nonlinear rate of decay through May.
|
||
Next, Bill studies the IV term structure for the Harley-Davidson ATMs
|
||
and finds the March has about a 19.2 percent IV, the April has a 23.3
|
||
percent IV, and the May has a 23 percent IV. March is the cheapest option
|
||
by IV standards. This is not necessarily a favorable quality for a short
|
||
candidate. Bill must weigh his assessment of all relevant information and
|
||
then decide which trade is best. With this type of a strategy, the benefits of
|
||
the higher theta can outweigh the disadvantages of selling the lower IV. In
|
||
this case, Bill may actually like selling the lower IV. He may infer that the
|
||
market believes Harley-Davidson will be less volatile during this period.
|
||
So far, Bill has been focusing his efforts on the 70 strike calls. If he trades
|
||
the March 70 covered call, he will have a net delta of 0.588 per contract.
|
||
That’s the negative 0.412 delta from shorting the call plus the 1.00 delta of
|
||
the stock. His indifference point if the trade is held until expiration is
|
||
$70.85. The indifference point is the point at which Bill would be
|
||
indifferent as to whether he held only the stock or the covered call. This is
|
||
figured by adding the strike price of $70 to the 0.85 premium. This is the
|
||
effective sale price of the stock if the call is assigned. If Bill wants more
|
||
potential for upside profit, he could sell a higher strike. He would have to
|
||
sell the April or May 75, since the March 75s are a zero bid. This would
|
||
give him a higher indifference point, and the upside profits would
|
||
materialize quickly if HOG moved higher, since the covered-call deltas
|
||
would be higher with the 75 calls. The April 75 covered-call net delta is
|
||
0.796 per contract (the stock delta of 1.00 minus the 0.204 delta of the call).
|
||
The May 75 covered-call delta is 0.751.
|
||
But Bill is neutral to only slightly bullish. In this case, he’d rather have
|
||
the higher premium—high theta is more desirable than high delta in this
|
||
situation. Bill buys 1,000 shares of Harley-Davidson at $69 and sells 10
|
||
Harley-Davidson March 70 calls at 0.85.
|
||
Bill also needs to plan his exit. To exit, he must study two things: an at-
|
||
expiration diagram and his greeks. Exhibit 5.8 shows the P&(L) at
|
||
expiration of the Harley-Davidson March 70 covered call. Exhibit 5.9
|
||
shows the greeks.
|
||
EXHIBIT 5.8 Harley-Davidson covered call.
|
||
EXHIBIT 5.9 Greeks for Harley-Davidson covered call (per contract).
|
||
Delta 0.591
|
||
Gamma−0.121
|
||
Theta 0.032
|
||
Vega −0.066
|
||
Taking It Off
|
||
If the trade works out perfectly for Bill, 22 days from now Harley-Davidson
|
||
will be trading right at $70. He’d profit on both delta and theta. If the trade
|
||
isn’t exactly perfect, but still good, Harley-Davidson will be anywhere
|
||
above $68.15 in 22 days. It’s the prospect that the trade may not be so good
|
||
at March expiration that occupies Bill’s thoughts, but a trader has to hope
|
||
for the best and plan for the worst.
|
||
If it starts to trend, Bill needs to react. The consequences to the stock’s
|
||
trending to the upside are not quite so dire, although he might be somewhat
|
||
frustrated with any lost opportunity above the indifference point. It’s the
|
||
downside risk that Bill will more vehemently guard against.
|
||
First, the same IV/vega considerations exist as they did in the previous
|
||
examples. In the event the trade is closed early, IV/vega may help or hinder
|
||
profitability. A rise in implied volatility will likely accompany a decline in
|
||
the stock price. This can bring Bill to his stop-loss sooner. Delta versus
|
||
theta however, is the major consideration. He will plan his exit price in
|
||
advance and cover when the planned exit price is reached.
|
||
There are more moving parts with the covered call than a naked option. If
|
||
Bill wants to close the position early, he can leg out, meaning close only
|
||
one leg of the trade (the call or the stock) at a time. If he legs out of the
|
||
trade, he’s likely to close the call first. The motivation for exiting a trade
|
||
early is to reduce risk. A naked call is hardly less risky than a covered call.
|
||
Another tactic Bill can use, and in this case will plan to use, is rolling the
|
||
call. When the March 70s expire, if Harley-Davidson is still in the same
|
||
range and his outlook is still the same, he will sell April calls to continue
|
||
the position. After the April options expire, he’ll plan to sell the Mays.
|
||
With this in mind, Bill may consider rolling into the Aprils before March
|
||
expiration. If it is close to expiration and Harley-Davidson is trading lower,
|
||
theta and delta will both have devalued the calls. At the point when options
|
||
are close to expiration and far enough OTM to be offered close to zero, say
|
||
0.05, the greeks and the pricing model become irrelevant. Bill must
|
||
consider in absolute terms if it is worth waiting until expiration to make
|
||
0.05. If there is a lot of time until expiration, the answer is likely to be no.
|
||
This is when Bill will be apt to roll into the Aprils. He’ll buy the March 70s
|
||
for a nickel, a dime, or maybe 0.15 and at the same time sell the Aprils at
|
||
the bid. This assumes he wants to continue to carry the position. If the roll
|
||
is entered as a single order, it is called a calendar spread or a time spread.
|
||
Covered Put
|
||
The last position in the family of basic volatility-selling strategies is the
|
||
covered put, sometimes referred to as selling puts and stock. In a covered
|
||
put, a trader sells both puts and stock on a one-to-one basis. The term
|
||
covered put is a bit of a misnomer, as the strategy changes from limited risk
|
||
to unlimited risk when short stock is added to the short put. A naked put can
|
||
produce only losses until the stock goes to zero—still a substantial loss.
|
||
Adding short stock means that above the strike gains on the put are limited,
|
||
while losses on the stock are unlimited. The covered put functions very
|
||
much like a naked call. In fact, they are synthetically equal. This concept
|
||
will be addressed further in the next chapter.
|
||
Let’s looks at another trader, Libby. Libby is an active trader who trades
|
||
several positions at once. Libby believes the overall market is in a range
|
||
and will continue as such over the next few weeks. She currently holds a
|
||
short stock position of 1,000 shares in Harley-Davidson. She is becoming
|
||
more neutral on the stock and would consider buying in her short if the
|
||
market dipped. She may consider entering into a covered-put position.
|
||
There is one caveat: Libby is leaving for a cruise in two weeks and does not
|
||
want to carry any positions while she is away. She decides she will sell the
|
||
covered put and actively manage the trade until her vacation. Libby will sell
|
||
10 Harley-Davidson March (22-day) 70 puts at 1.85 against her short 1,000
|
||
shares of Harley-Davidson, which is trading at $69 per share.
|
||
She knows that her maximum profit if the stock declines and assignment
|
||
occurs will be $850. That’s 0.85 × $100 × 10 contracts. Win or lose, she
|
||
will close the position in two weeks when there are only eight days until
|
||
expiration. To trade this covered put she needs to watch her greeks.
|
||
Exhibit 5.10 shows the greeks for the Harley-Davidson 70-strike covered
|
||
put.
|
||
EXHIBIT 5.10 Greeks for Harley-Davidson covered put (per contract).
|
||
Delta −0.419
|
||
Gamma−0.106
|
||
Theta 0.031
|
||
Vega −0.066
|
||
Libby is really focusing on theta. It is currently about $0.03 per day but
|
||
will increase if the put stays close-to-the-money. In two weeks, the time
|
||
premium will have decayed significantly. A move downward will help, too,
|
||
as the −0.419 delta indicates. Exhibit 5.11 displays an array of theoretical
|
||
values of the put at eight days until expiration as the stock price changes.
|
||
EXHIBIT 5.11 HOG 70 put values at 8 days to expiry.
|
||
As long as Harley-Davidson stays below the strike price, Libby can look
|
||
at her put from a premium-over-parity standpoint. Below the strike, the
|
||
intrinsic value of the put doesn’t matter too much, because losses on
|
||
intrinsic value are offset by gains on the stock. For Libby, all that really
|
||
matters is the time value. She sold the puts at 0.85 over parity. If Harley-
|
||
Davidson is trading at $68 with eight days to go, she can buy her puts back
|
||
for 0.12 over parity. That’s a 73-cent profit, or $730 on her 10 contracts.
|
||
This doesn’t account for any changes in the time value that may occur as a
|
||
result of vega, but vega will be small with Harley-Davidson at $68 and
|
||
eight days to go. At this point, she would likely close down the whole
|
||
position—buying the puts and buying the stock—to take a profit on a
|
||
position that worked out just about exactly as planned.
|
||
Her risk, though, is to the upside. A big rally in the stock can cause big
|
||
losses. From a theoretical standpoint, losses are potentially unlimited with
|
||
this type of trade. If the stock is above the strike, she needs to have a mental
|
||
stop order in mind and execute the closing order with discipline.
|
||
Curious Similarities
|
||
These basic volatility-selling strategies are fairly simple in nature. If the
|
||
trader believes a stock will not rise above a certain price, the most
|
||
straightforward way to trade the forecast is to sell a call. Likewise, if the
|
||
trader believes the stock will not go below a certain price he can sell a put.
|
||
The covered call and covered put are also ways to generate income on long
|
||
or short stock positions that have these same price thresholds. In fact, the
|
||
covered call and covered put have some curious similarities to the naked
|
||
put and naked call. The similarities between the two pairs of positions are
|
||
no coincidence. The following chapter sheds light on these similarities.
|
||
CHAPTER 6
|
||
Put-Call Parity and Synthetics
|
||
In order to understand more complex spread strategies involving two or
|
||
more options, it is essential to understand the arbitrage relationship of the
|
||
put-call pair. Puts and calls of the same month and strike on the same
|
||
underlying have prices that are defined in a mathematical relationship. They
|
||
also have distinctly related vegas, gammas, thetas, and deltas. This chapter
|
||
will show how the metrics of these options are interrelated. It will also
|
||
explore synthetics and the idea that by adding stock to a position, a trader
|
||
may trade with indifference either a call or a put to the same effect.
|
||
Put-Call Parity Essentials
|
||
Before the creation of the Black-Scholes model, option pricing was hardly
|
||
an exact science. Traders had only a few mathematical tools available to
|
||
compare the relative prices of options. One such tool, put-call parity, stems
|
||
from the fact that puts and calls on the same class sharing the same month
|
||
and strike can have the same functionality when stock is introduced.
|
||
For example, traders wanting to own a stock with limited risk can buy a
|
||
married put: long stock and a long put on a share-for-share basis. The
|
||
traders have infinite profit potential, and the risk of the position is limited
|
||
below the strike price of the option. Conceptually, long calls have the same
|
||
risk/reward profile—unlimited profit potential and limited risk below the
|
||
strike. Exhibit 6.1 is an overview of the at-expiration diagrams of a married
|
||
put and a long call.
|
||
EXHIBIT 6.1 Long call vs. long stock + long put (married put).
|
||
Married puts and long calls sharing the same month and strike on the
|
||
same security have at-expiration diagrams with the same shape. They have
|
||
the same volatility value and should trade around the same implied
|
||
volatility (IV). Strategically, these two positions provide the same service to
|
||
a trader, but depending on margin requirements, the married put may
|
||
require more capital to establish, because the trader must buy not just the
|
||
option but also the stock.
|
||
The stock component of the married put could be purchased on margin.
|
||
Buying stock on margin is borrowing capital to finance a stock purchase.
|
||
This means the trader has to pay interest on these borrowed funds. Even if
|
||
the stock is purchased without borrowing, there is opportunity cost
|
||
associated with the cash used to pay for the stock. The capital is tied up. If
|
||
the trader wants to use funds to buy another asset, he will have to borrow
|
||
money, which will incur an interest obligation. Furthermore, if the trader
|
||
doesn’t invest capital in the stock, the capital will rest in an interest-bearing
|
||
account. The trader forgoes that interest when he buys a stock. However the
|
||
trader finances the purchase, there is an interest cost associated with the
|
||
transaction.
|
||
Both of these positions, the long call and the married put, give a trader
|
||
exposure to stock price advances above the strike price. The important
|
||
difference between the two trades is the value of the stock below the strike
|
||
price—the part of the trade that is not at risk in either the long call or the
|
||
married put. On this portion of the invested capital, the trader pays interest
|
||
with the married put (whether actually or in the form of opportunity cost).
|
||
This interest component is a pricing consideration that adds cost to the
|
||
married put and not the long call.
|
||
So if the married put is a more expensive endeavor than the long call
|
||
because of the interest paid on the investment portion that is below the
|
||
strike, why would anyone buy a married put? Wouldn’t traders instead buy
|
||
the less expensive—less capital intensive—long call? Given the additional
|
||
interest expense, they would rather buy the call. This relates to the concept
|
||
of arbitrage. Given two effectively identical choices, rational traders will
|
||
choose to buy the less expensive alternative. The market as a whole would
|
||
buy the calls, creating demand which would cause upward price pressure on
|
||
the call. The price of the call would rise until its interest advantage over the
|
||
married put was gone. In a robust market with many savvy traders,
|
||
arbitrage opportunities don’t exist for very long.
|
||
It is possible to mathematically state the equilibrium point toward which
|
||
the market forces the prices of call and put options by use of the put-call
|
||
parity. As shown in Chapter 2, the put-call parity states
|
||
|
||
where c is the call premium, PV(x) is the present value of the strike
|
||
price, p is the put premium and s is the stock price.
|
||
Another, less academic and more trader-friendly way of stating this
|
||
equation is
|
||
where Interest is calculated as
|
||
Interest = Strike × Interest Rate ×(Days to Expiration/365) 1
|
||
The two versions of the put-call parity stated here hold true for European
|
||
options on non-dividend-paying stocks.
|
||
Dividends
|
||
Another difference between call and married-put values is dividends. A call
|
||
option does not extend to its owner the right to receive a dividend payment.
|
||
Traders, however, who are long a put and long stock are entitled to a
|
||
dividend if it is the corporation’s policy to distribute dividends to its
|
||
shareholders.
|
||
An adjustment must be made to the put-call parity to account for the
|
||
possibility of a dividend payment. The equation must be adjusted to account
|
||
for the absence of dividends paid to call holders. For a dividend-paying
|
||
stock, the put-call parity states
|
||
The interest advantage and dividend disadvantage of owning a call is
|
||
removed from the market by arbitrageurs. Ultimately, that is what is
|
||
expressed in the put-call parity. It’s a way to measure the point at which the
|
||
arbitrage opportunity ceases to exist. When interest and dividends are
|
||
factored in, a long call is an equal position to a long put paired with long
|
||
stock. In options nomenclature, a long put with long stock is a synthetic
|
||
long call. Algebraically rearranging the above equation:
|
||
The interest and dividend variables in this equation are often referred to
|
||
as the basis. From this equation, other synthetic relationships can be
|
||
algebraically derived, like the synthetic long put.
|
||
A synthetic long put is created by buying a call and selling (short) stock.
|
||
The at-expiration diagrams in Exhibit 6.2 show identical payouts for these
|
||
two trades.
|
||
EXHIBIT 6.2 Long put vs. long call + short stock.
|
||
The concept of synthetics can become more approachable when studied
|
||
from the perspective of delta as well. Take the 50-strike put and call listed
|
||
on a $50 stock. A general rule of thumb in the put-call pair is that the call
|
||
delta plus the put delta equals 1.00 when the signs are ignored. If the 50 put
|
||
in this example has a −0.45 delta, the 50 call will have a 0.55 delta. By
|
||
combining the long call (0.55 delta) with short stock (–1.00 delta), we get a
|
||
synthetic long put with a −0.45 delta, just like the actual put. The
|
||
directional risk is the same for the synthetic put and the actual put.
|
||
A synthetic short put can be created by selling a call of the same month
|
||
and strike and buying stock on a share-for-share basis (i.e., a covered call).
|
||
This is indicated mathematically by multiplying both sides of the put-call
|
||
parity equation by −1:
|
||
The at-expiration diagrams, shown in Exhibit 6.3 , are again conceptually
|
||
the same.
|
||
EXHIBIT 6.3 Short put vs. short call + long stock.
|
||
A short (negative) put is equal to a short (negative) call plus long stock,
|
||
after the basis adjustment. Consider that if the put is sold instead of buying
|
||
stock and selling a call, the interest that would otherwise be paid on the cost
|
||
of the stock up to the strike price is a savings to the put seller. To balance
|
||
the equation, the interest benefit of the short put must be added to the call
|
||
side (or subtracted from the put side). It is the same with dividends. The
|
||
dividend benefit of owning the stock must be subtracted from the call side
|
||
to make it equal to the short put side (or added to the put side to make it
|
||
equal the call side).
|
||
The same delta concept applies here. The short 50-strike put in our
|
||
example would have a 0.45 delta. The short call would have a −0.55 delta.
|
||
Buying one hundred shares along with selling the call gives the synthetic
|
||
short put a net delta of 0.45 (–0.55 + 1.00).
|
||
Similarly, a synthetic short call can be created by selling a put and selling
|
||
(short) one hundred shares of stock. Exhibit 6.4 shows a conceptual
|
||
overview of these two positions at expiration.
|
||
EXHIBIT 6.4 Short call vs. short put + short stock.
|
||
Put-call parity can be manipulated as shown here to illustrate the
|
||
composition of the synthetic short call.
|
||
Most professional traders earn a short stock rebate on the proceeds they
|
||
receive when they short stock—an advantage to the short-put–short-stock
|
||
side of the equation. Additionally, short-stock sellers must pay dividends on
|
||
the shares they are short—a liability to the married-put seller. To make all
|
||
things equal, one subtracts interest and adds dividends to the put side of the
|
||
equation.
|
||
Comparing Synthetic Calls and Puts
|
||
The common thread among the synthetic positions explained above is that,
|
||
for a put-call pair, long options have synthetic equivalents involving long
|
||
options, and short options have synthetic equivalents involving short
|
||
options. After accounting for the basis, the four basic synthetic option
|
||
positions are:
|
||
Because a call or put position is interchangeable with its synthetic
|
||
position, an efficient market will ensure that the implied volatility is closely
|
||
related for both. For example, if a long call has an IV of 25 percent, the
|
||
corresponding put should have an IV of about 25 percent, because the long
|
||
put can easily be converted to a synthetic long call and vice versa. The
|
||
greeks will be similar for synthetically identical positions, too. The long
|
||
options and their synthetic equivalents will have positive gamma and vega
|
||
with negative theta. The short options and their synthetics will have
|
||
negative gamma and vega with positive theta.
|
||
American-Exercise Options
|
||
Put-call parity was designed for European-style options. The early exercise
|
||
possibility of American-style options gums up the works a bit. Because a
|
||
call (put) and a synthetic call (put) are functionally the same, it is logical to
|
||
assume that the implied volatility and the greeks for both will be exactly the
|
||
same. This is not necessarily true with American-style options. However,
|
||
put-call parity may still be useful with American options when the
|
||
limitations of the equation are understood. With at-the-money American-
|
||
exercise options, the differences in the greeks for a put-call pair are subtle.
|
||
Exhibit 6.5 is a comparison of the greeks for the 50-strike call and the 50-
|
||
strike put with the underlying at $50 and 66 days until expiration.
|
||
EXHIBIT 6.5 Greeks for a 50-strike put-call pair on a $50 stock.
|
||
Call Put
|
||
Delta 0.5540.457
|
||
Gamma0.0750.078
|
||
Theta 0.0200.013
|
||
Vega 0.0840.084
|
||
The examples used earlier in this chapter in describing the deltas of
|
||
synthetics were predicated on the rule of thumb that the absolute values of
|
||
call and put deltas add up to 1.00. To be a bit more realistic, consider that
|
||
because of American exercise, the absolute delta values of put-call pairs
|
||
don’t always add up to 1.00. In fact, Exhibit 6.5 shows that the call has
|
||
closer to a 0.554 delta. The put struck at the same price then has a 0.457
|
||
delta. By selling 100 shares against the long call, we can create a combined-
|
||
position delta (call delta plus stock delta) that is very close to the put’s
|
||
delta. The delta of this synthetic put is −0.446 (0.554 − 1.00). The delta of a
|
||
put will always be similar to the delta of its corresponding synthetic put.
|
||
This is also true with call–synthetic-call deltas. This relationship
|
||
mathematically is
|
||
|
||
This holds true whether the options are in-, at-, or out-of-the-money. For
|
||
example, with a stock at $54, the 50-put would have a −0.205 delta and the
|
||
call would have a 0.799 delta. Selling 100 shares against the call to create
|
||
the synthetic put yields a net delta of −0.201.
|
||
If long or short stock is added to a call or put to create a synthetic, delta
|
||
will be the only greek affected. With that in mind, note the other greeks
|
||
displayed in Exhibit 6.5 —especially theta. Proportionally, the biggest
|
||
difference in the table is in theta. The disparity is due in part to interest.
|
||
When the effects of the interest component outweigh the effects of the
|
||
dividend, the time value of the call can be higher than the time value of the
|
||
put. Because the call must lose more premium than the put by expiration,
|
||
the theta of the call must be higher than the theta of the put.
|
||
American exercise can also cause the option prices in put-call parity to
|
||
not add up. Deep in-the-money (ITM) puts can trade at parity while the
|
||
corresponding call still has time value. The put-call equation can be
|
||
unbalanced. The same applies to calls on dividend-paying stocks as the
|
||
dividend date approaches. When the date is imminent, calls can trade close
|
||
to parity while the puts still have time value. The role of dividends will be
|
||
discussed further in Chapter 8.
|
||
Synthetic Stock
|
||
Not only can synthetic calls and puts be derived by manipulation of put-call
|
||
parity, but synthetic positions for the other security in the equation—stock
|
||
—can be derived, as well. By isolating stock on one side of the equation,
|
||
the formula becomes
|
||
After accounting for interest and dividends, buying a call and selling a put
|
||
of the same strike and time to expiration creates the equivalent of a long
|
||
stock position. This is called a synthetic stock position, or a combo. After
|
||
accounting for the basis, the equation looks conceptually like this:
|
||
This is easy to appreciate when put-call parity is written out as it is here.
|
||
It begins to make even more sense when considering at-expiration diagrams
|
||
and the greeks.
|
||
Exhibit 6.6 illustrates a long stock position compared with a long call
|
||
combined with a short put position.
|
||
EXHIBIT 6.6 Long stock vs. long call + short put.
|
||
A quick glance at these two strategies demonstrates that they are the
|
||
same, but think about why. Consider the synthetic stock position if both
|
||
options are held until expiration. The long call gives the trader the right to
|
||
buy the stock at the strike price. The short put gives the trader the obligation
|
||
to buy the stock at the same strike price. It doesn’t matter what the strike
|
||
price is. As long as the strike is the same for the call and the put, the trader
|
||
will have a long position in the underlying at the shared strike at expiration
|
||
when exercise or assignment occurs.
|
||
The options in this example are 50-strike options. At expiration, the trader
|
||
can exercise the call to buy the underlying at $50 if the stock is above the
|
||
strike. If the underlying is below the strike at expiration, he’ll get assigned
|
||
on the put and buy the stock at $50. If the stock is bought, whether by
|
||
exercise or assignment, the effective price of the potential stock purchase,
|
||
however, is not necessarily $50.
|
||
For example, if the trader bought one 50-strike call at 3.50 and sold one
|
||
50-strike put at 1.50, he will effectively purchase the underlying at $52
|
||
upon exercise or assignment. Why? The trader paid a net of $2 to get a long
|
||
position in the stock synthetically (3.50 of call premium debited minus 1.50
|
||
of put premium credited). Whether the call or the put is ITM, the effective
|
||
purchase price of the stock will always be the strike price plus or minus the
|
||
cost of establishing the synthetic, in this case, $52.
|
||
The question that begs to be asked is: would the trader rather buy the
|
||
stock or pay $2 to have the same market exposure as long stock?
|
||
Arbitrageurs in the market (with the help of the put-call parity) ensure that
|
||
neither position—long stock or synthetic long stock—is better than the
|
||
other.
|
||
For example, assume a stock is trading at $51.54. With 71 days until
|
||
expiration, 26.35 IV, a 5 percent interest rate, and no dividends, the 50-
|
||
strike call is theoretically worth 3.50, and the 50-strike put is theoretically
|
||
worth 1.50. Exhibit 6.7 charts the synthetic stock versus the actual stock
|
||
when there are 71 days until expiration.
|
||
EXHIBIT 6.7 Long stock and synthetic long stock with 71 days to
|
||
expiration.
|
||
Looking at this exhibit, it appears that being long the actual stock
|
||
outperforms being long the stock synthetically. If the stock is purchased at
|
||
$51.54, it need only rise a penny higher to profit (in the theoretical world
|
||
where traders do not pay commissions on transactions). If the synthetic is
|
||
purchased for $2, the stock needs to rise $0.46 to break even—an apparent
|
||
disadvantage. This figure, however, does not include interest.
|
||
The synthetic stock offers the same risk/reward as actually being long the
|
||
stock. There is a benefit, from the perspective of interest, to paying only $2
|
||
for this exposure rather than $51.54. The interest benefit here is about
|
||
$0.486. We can find this number by calculating the interest as we did earlier
|
||
in the chapter. Interest, again, is computed as the strike price times the
|
||
interest rate times the number of days to expiration divided by the number
|
||
of days in a year. The formula is as follows:
|
||
Inputting the numbers from this example:
|
||
The $0.486 of interest is about equal to the $0.46 disparity between the
|
||
diagrams of the stock and the synthetic stock with 71 days until expiration.
|
||
The difference is due mainly to rounding and the early-exercise potential of
|
||
the American put. In mathematical terms
|
||
The synthetic long stock is approximately equal to the long stock position
|
||
when considering the effect of interest. The two lines in Exhibit 6.7 —
|
||
representing stock and synthetic stock—would converge with each passing
|
||
day as the calculated interest decreases.
|
||
This equation works as well for a synthetic short stock position; reversing
|
||
the signs reveals the synthetic for short stock.
|
||
Or, in this case,
|
||
Shorting stock at $51.54 is about equal to selling the 50 call and buying
|
||
the 50 put for a $2 credit based on the interest of 0.486 computed on the 50
|
||
strike. Again, the $0.016 disparity between the calculated interest and the
|
||
actual difference between the synthetic value and the stock price is a
|
||
function of rounding and early exercise. More on this in the “Conversions
|
||
and Reversals” section.
|
||
Synthetic Stock Strategies
|
||
Ultimately, when we roll up our sleeves and get down to the nitty-gritty,
|
||
options trading is less about having another alternative for trading the
|
||
direction of the underlying than it is about trading the greeks. Different
|
||
strategies allow traders to exploit different facets of option pricing. Some
|
||
strategies allow traders to trade volatility. Some focus mainly on theta.
|
||
Many of the strategies discussed in this section present ways for a trader to
|
||
distill risk down mostly to interest rate exposure.
|
||
Conversions and Reversals
|
||
When calls and puts are combined to create synthetic stock, the main
|
||
differences are the interest rate and dividends. This is important because the
|
||
risks associated with interest and dividends can be isolated, and ultimately
|
||
traded, when synthetic stock is combined with the underlying. There are
|
||
two ways to combine synthetic stock with its underlying security: a
|
||
conversion and a reversal.
|
||
Conversion
|
||
A conversion is a three-legged position in which a trader is long stock, short
|
||
a call, and long a put. The options share the same month and strike price.
|
||
By most metrics, this is a very flat position. A trader with a conversion is
|
||
long the stock and, at the same time, synthetically short the same stock.
|
||
Consider this from the perspective of delta. In a conversion, the trader is
|
||
long 1.00 deltas (the long stock) and short very close to 1.00 deltas (the
|
||
synthetic short stock). Conversions have net flat deltas.
|
||
The following is a simple example of a typical conversion and the
|
||
corresponding deltas of each component.
|
||
Short one 35-strike call:−0.63 delta
|
||
Long one 35-strike put:−0.37 delta
|
||
Long 100 shares: 1.00 delta
|
||
0.00 delta
|
||
The short call contributes a negative delta to the position, in this case,
|
||
−0.63. The long put also contributes a negative delta, −0.37. The combined
|
||
delta of the synthetic stock is −1.00 in this example, which is like being
|
||
short 100 shares of stock. When the third leg of the spread is added, the
|
||
long 100 shares, it counterbalances the synthetic. The total delta for the
|
||
conversion is zero.
|
||
Most of the conversion’s other greeks are pretty flat as well. Gamma,
|
||
theta, and vega are similar for the call and the put in the conversion,
|
||
because they have the same expiration month and strike price. Because the
|
||
trader is selling one option and buying another—a call and a put,
|
||
respectively—with the same month and strike, the greeks come very close
|
||
to offsetting each other. For all intents and purposes, the trader is out of the
|
||
primary risks of the position as measured by greeks when a position is
|
||
converted. Let’s look at a more detailed example.
|
||
A trader executes the following trade (for the purposes of this example,
|
||
we assume the stock pays no dividend and the trade is executed at fair
|
||
value):
|
||
Sell one 71-day 50 call at 3.50
|
||
Buy one 71-day 50 put at 1.50
|
||
Buy 100 shares at $51.54
|
||
The trader buys the stock at $51.54 and synthetically sells the stock at
|
||
$52. The synthetic price is computed as −3.50 + 1.50 − 50. Therefore, the
|
||
stock is sold synthetically at $0.46 over the actual stock price.
|
||
Exhibit 6.8 shows the analytics for the conversion.
|
||
EXHIBIT 6.8 Conversion greeks.
|
||
This position has very subtle sensitivity to the greeks. The net delta for
|
||
the spread has a very slightly negative bias. The bias is so small it is
|
||
negligible to most traders, except professionals trading very large positions.
|
||
Why does this negative delta bias exist? Mathematically, the synthetic’s
|
||
delta can be higher with American options than with their European
|
||
counterparts because of the possibility of early exercise of the put. This
|
||
anomaly becomes more tangible when we consider the unique directional
|
||
risk associated with this trade.
|
||
In this example, the stock is synthetically sold at $0.46 over the price at
|
||
which the stock is bought. If the stock declines significantly in value before
|
||
expiration, the put will, at some point, trade at parity while the call loses all
|
||
its time value. In this scenario, the value of the synthetic stock will be short
|
||
at effectively the same price as the actual stock price. For example, if the
|
||
stock declines to $35 per share then the numbers are as follows:
|
||
or
|
||
With American options, a put this far in-the-money with less than 71 days
|
||
until expiry will be all intrinsic value. Interest, in this case, will not factor
|
||
into the put’s value, because the put can be exercised. By exercising the put,
|
||
both the long stock leg and the long put leg can be closed for even money,
|
||
leaving only the theoretically worthless call. The stock-synthetic spread is
|
||
sold at 0.46 and essentially bought at zero when the put is exercised. If the
|
||
put is exercised before expiration, the profit potential is 0.46 minus the
|
||
interest calculated between the trade date and the day the put is exercised.
|
||
If, however, the conversion is held until expiration, the $0.46 is negated by
|
||
the $0.486 of interest incurred from holding long stock over the entire 71-
|
||
day period, hence the trader’s desire to see the stock decline before
|
||
expiration, and thus the negative bias toward delta.
|
||
This is, incidentally, why the synthetic price (0.46 over the stock price)
|
||
does not exactly equal the calculated value of the interest (0.486). The
|
||
trader can exercise the put early if the stock declines and capitalize on the
|
||
disparity between the interest calculated when the conversion was traded
|
||
and the actual interest calculation given the shorter time frame. The model
|
||
values the synthetic at a little less than the interest value would indicate—in
|
||
this case $0.46 instead of $0.486.
|
||
The gamma of this trade is fairly negligible. The theta is slightly positive.
|
||
Rho is the figure that deserves the most attention. Rho is the change in an
|
||
option’s price given a change in the interest rate.
|
||
The −0.090 rho of the conversion indicates that if the interest rate rises
|
||
one percentage point, the position as a whole loses $0.09. Why? The
|
||
financing of the position gets more expensive as the interest rate rises. The
|
||
trader would have to pay more in interest to carry the long stock. In this
|
||
example, if interest rises by one percentage point, the synthetic stock, which
|
||
had an effective short price of $0.46 over the price of the long stock before
|
||
the interest rate increase, will be $0.55 over the price of the long stock
|
||
afterward. If, however, the interest rate declines by one percentage point,
|
||
the trader profits $0.09, as the synthetic is repriced by the market to $0.37
|
||
over the stock price. The lower the interest rate, the less expensive it is to
|
||
finance the long stock. This is proven mathematically by put-call parity.
|
||
Negative rho indicates a bearish position on the interest rate; the trader
|
||
wants it to go lower. Positive rho is a bullish interest rate position.
|
||
But a one-percentage-point change in the interest rate in one day is a big
|
||
and uncommon change. The question is: is rho relevant? That depends on
|
||
the type of position and the type of trader. A 0.090 rho would lead to a
|
||
0.0225 profit-and-loss (P&(L)) change per one lot conversion on a 25-basis-
|
||
point, or quarter percent, change. That’s just $2.25 per spread. This
|
||
incremental profit or loss, however, can be relevant to professional traders
|
||
like market makers. They trade very large positions with the aspiration of
|
||
making small incremental profits on each trade. A market maker with a
|
||
5,000-lot conversion would stand to make or lose $11,250, given a quarter-
|
||
percentage-point change in interest rate and a 0.090 rho.
|
||
The Mind of a Market Maker
|
||
Market makers are among the only traders who can trade conversions and
|
||
reversals profitably, because of the size of their trades and the fact that they
|
||
can buy the bid and sell the offer. Market makers often attempt to leg into
|
||
and out of conversions (and reversals). Given the conversion in this
|
||
example, a market maker may set out to sell calls and in turn buy stock to
|
||
hedge the call’s delta risk (this will be covered in Chapters 12 and 17), then
|
||
buy puts and the rest of the stock to create a balanced conversion: one call
|
||
to one put to one hundred shares. The trader may try to put on the
|
||
conversion in the previous example for a total of $0.50 over the price of the
|
||
long stock instead of the $0.46 it’s worth. He would then try to leg out of
|
||
the trade for less, say $0.45 over the stock, with the goal of locking in a
|
||
$0.05 profit per spread on the whole trade.
|
||
Reversal
|
||
A reversal, or reverse conversion, is simply the opposite of the conversion:
|
||
buy call, sell put, and sell (short) stock. A reversal can be executed to close
|
||
a conversion, or it can be an opening transaction. Using the same stock and
|
||
options as in the previous example, a trader could establish a reversal as
|
||
follows:
|
||
Buy one 71-day 50 call at 3.50
|
||
Sell one 71-day 50 put at 1.50
|
||
Sell 100 shares at 51.54
|
||
The trader establishes a short position in the stock at $51.54 and a long
|
||
synthetic stock position effectively at $52.00. He buys the stock
|
||
synthetically at $0.46 over the stock price, again assuming the trade can be
|
||
executed at fair value. With the reversal, the trader has a bullish position on
|
||
interest rates, which is indicated by a positive rho.
|
||
In this example, the rho for this position is 0.090. If interest rates rise one
|
||
percentage point, the synthetic stock (which the trader is long) gains nine
|
||
cents in value relative to the stock. The short stock rebate on the short stock
|
||
leg earns more interest at a higher interest rate. If rates fall one percentage
|
||
point, the synthetic long stock loses $0.09. The trader earns less interest
|
||
being short stock given a lower interest rate.
|
||
With the reversal, the fact that the put can be exercised early is a risk.
|
||
Since the trader is short the put and short stock, he hopes not to get
|
||
assigned. If he does, he misses out on the interest he planned on collecting
|
||
when he put on the reversal for $0.46 over.
|
||
Pin Risk
|
||
Conversions and reversals are relatively low-risk trades. Rho and early
|
||
exercise are relevant to market makers and other arbitrageurs, but they are
|
||
among the lowest-risk positions they are likely to trade. There is one
|
||
indirect risk of conversions and reversals that can be of great concern to
|
||
market makers around expiration: pin risk. Pin risk is the risk of not
|
||
knowing for certain whether an option will be assigned. To understand this
|
||
concept, let’s revisit the mind of a market maker.
|
||
Recall that market makers have two primary functions:
|
||
1. Buy the bid or sell the offer.
|
||
2. Manage risk.
|
||
When institutional or retail traders send option orders to an exchange
|
||
(through a broker), market makers are usually the ones with whom they
|
||
trade. Customers sell the bid; the market makers buy the bid. Customers
|
||
buy the offer; the market makers sell the offer. The first and arguably easier
|
||
function of market makers is accomplished whenever a marketable order is
|
||
sent to the exchange.
|
||
Managing risk can get a bit hairy. For example, once the market makers
|
||
buy April 40 calls, their first instinct is to hedge by selling stock to become
|
||
delta neutral. Market makers are almost always delta neutral, which
|
||
mitigates the direction risk. The next step is to mitigate theta, gamma, and
|
||
vega risk by selling options. The ideal options to sell are the same calls that
|
||
were bought—that is, get out of the trade. The next best thing is to sell the
|
||
April 40 puts and sell more stock. In this case, the market makers have
|
||
established a reversal and thereby have very little risk. If they can lock in
|
||
the reversal for a small profit, they have done their job.
|
||
What happens if the market makers still have the reversal in inventory at
|
||
expiration? If the stock is above the strike price—40, in this case—the puts
|
||
expire, the market makers exercise the calls, and the short stock is
|
||
consequently eliminated. The market makers are left with no position,
|
||
which is good. They’re delta neutral. If the stock is below 40, the calls
|
||
expire, the puts get assigned, and the short stock is consequently eliminated.
|
||
Again, no position. But what if the stock is exactly at $40? Should the calls
|
||
be exercised? Will the puts get assigned? If the puts are assigned, the
|
||
traders are left with no short stock and should let the calls expire without
|
||
exercising so as not to have a long delta position after expiration. If the puts
|
||
are not assigned, they should exercise the calls to get delta flat. It’s also
|
||
possible that only some of the puts will be assigned.
|
||
Because they don’t know how many, if any, of the puts will be assigned,
|
||
the market makers have pin risk. To avoid pin risk, market makers try to
|
||
eliminate their position if they have conversions or reversals close to
|
||
expiration.
|
||
Boxes and Jelly Rolls
|
||
There are two other uses of synthetic stock positions that form conventional
|
||
strategies: boxes and rolls.
|
||
Boxes
|
||
When long synthetic stock is combined with short synthetic stock on the
|
||
same underlying within the same expiration cycle but with a different strike
|
||
price, the resulting position is known as a box. With a box, a trader is
|
||
synthetically both long and short the stock. The two positions, for all intents
|
||
and purposes, offset each other directionally. The risk of stock-price
|
||
movement is almost entirely avoided. A study of the greeks shows that the
|
||
delta is close to zero. Gamma, theta, vega, and rho are also negligible.
|
||
Here’s an example of a 60–70 box for April options:
|
||
Short 1 April 60 call
|
||
Long 1 April 60 put
|
||
Long 1 April 70 call
|
||
Short 1 April 70 put
|
||
In this example, the trader is synthetically short the 60-strike and, at the
|
||
same time, synthetically long the 70-strike. Exhibit 6.9 shows the greeks.
|
||
EXHIBIT 6.9 Box greeks.
|
||
Aside from the risks associated with early exercise implications, this
|
||
position is just about totally flat. The near-1.00 delta on the long synthetic
|
||
stock struck at 60 is offset by the near-negative-1.00 delta of the short
|
||
synthetic struck at 70. The tiny gammas and thetas of both combos are
|
||
brought closer to zero when they are spread against each another. Vega is
|
||
zero. And the bullish interest rate sensitivity of the long combo is nearly all
|
||
offset by the bearish interest sensitivity of the short combo. The stock can
|
||
move, time can pass, volatility and interest can change, and there will be
|
||
very little effect on the trader’s P&(L). The question is: Why would
|
||
someone trade a box?
|
||
Market makers accumulate positions in the process of buying bids and
|
||
selling offers. But they want to eliminate risk. Ideally, they try to be flat the
|
||
strike —meaning have an equal number of calls and puts at each strike
|
||
price, whether through a conversion or a reversal. Often, they have a
|
||
conversion at one strike and a reversal at another. The stock positions for
|
||
these cancel each other out and the trader is left with only the four option
|
||
legs—that is, a box. They can eliminate pin risk on both strikes by trading
|
||
the box as a single trade to close all four legs. Another reason for trading a
|
||
box has to do with capital.
|
||
Borrowing and Lending Money
|
||
The first thing to consider is how this spread is priced. Let’s look at another
|
||
example of a box, the October 50–60 box.
|
||
Long 1 October 60 call
|
||
Short 1 October 60 put
|
||
Short 1 October 70 call
|
||
Long 1 October 70 put
|
||
A trader with this position is synthetically long the stock at $60 and short
|
||
the stock at $70. That sounds like $10 in the bank. The question is: How
|
||
much would a trader be willing to pay for the right to $10? And for how
|
||
much would someone be willing to sell it? At face value, the obvious
|
||
answer is that the equilibrium point is at $10, but there is one variable that
|
||
must be factored in: time.
|
||
In this example, assume that the October call has 90 days until expiration
|
||
and the interest rate is 6 percent. A rational trader would not pay $10 today
|
||
for the right to have $10 90 days from now. That would effectively be like
|
||
loaning the $10 for 90 days and not receiving interest—A losing
|
||
proposition! The trader on the other side of this box would be happy to
|
||
enter into the spread for $10. He would have interest-free use of $10 for 90
|
||
days. That’s free money! Certainly, there is interest associated with the cost
|
||
of carrying the $10. In this case, the interest would be $0.15.
|
||
This $0.15 is discounted from the price of the $10 box. In fact, the
|
||
combined net value of the options composing the box should be about 9.85
|
||
—with differences due mainly to rounding and the early exercise possibility
|
||
for American options.
|
||
A trader buying this box—that is, buying the more ITM call and more
|
||
ITM put—would expect to pay $0.15 below the difference between the
|
||
strike prices. Fair value for this trade is $9.85. The seller of this box—the
|
||
trader selling the meatier options and buying the cheaper ones—would
|
||
concede up to $0.15 on the credit.
|
||
Jelly Rolls
|
||
A jelly roll, or simply a roll, is also a spread with four legs and a
|
||
combination of two synthetic stock trades. In a box, the difference between
|
||
the synthetics is the strike price; in a roll, it’s the contract month. Here’s an
|
||
example:
|
||
Long 1 April 50 call
|
||
Short 1 April 50 put
|
||
Short 1 May 50 call
|
||
Long 1 May 50 put
|
||
The options in this spread all share the same strike price, but they involve
|
||
two different months—April and May. In this example, the trader is long
|
||
synthetic stock in April and short synthetic stock in May. Like the
|
||
conversion, reversal, and box, this is a mostly flat position. Delta, gamma,
|
||
theta, vega, and even rho have only small effects on a jelly roll, but like the
|
||
others, this spread serves a purpose.
|
||
A trader with a conversion or reversal can roll the option legs of the
|
||
position into a month with a later expiration. For example, a trader with an
|
||
April 50 conversion in his inventory (short the 50 call, long the 50 put, long
|
||
stock) can avoid pin risk as April expiration approaches by trading the roll
|
||
from the above example. The long April 50 call and short April 50 put
|
||
cancel out the current option portion of the conversion leaving only the
|
||
stock. Selling the May 50 calls and buying the May 50 puts reestablishes
|
||
the conversion a month farther out.
|
||
Another reason for trading a roll has to do with interest. The roll in this
|
||
example has positive exposure to rho in April and negative exposure to rho
|
||
in May. Based on a trader’s expectations of future changes in interest rates,
|
||
a position can be constructed to exploit opportunities in interest.
|
||
Theoretical Value and the Interest
|
||
Rate
|
||
The main focus of the positions discussed in this chapter is fluctuations in
|
||
the interest rate. But which interest rate? That of 30-year bonds? That of 10-
|
||
or 5-year notes? Overnight rates? The federal funds rate? In the theoretical
|
||
world, the answer to this question is not really that important. Professors
|
||
simply point to the riskless rate and continue with their lessons. But when
|
||
putting strategies like these into practice, choosing the right rate makes a
|
||
big difference. To answer the question of which interest rate, we must
|
||
consider exactly what the rates represent from the standpoint of an
|
||
economist. Therefore, we must understand how an economist makes
|
||
arguments—by making assumptions.
|
||
Take the story of the priest, the physicist, and the economist stranded on a
|
||
desert island with nothing to eat except a can of beans. The problem is, the
|
||
can is sealed. In order to survive, they must figure out how to open the can.
|
||
The priest decides he will pray for the can to be opened by means of a
|
||
miracle. He prays for hours, but, alas, the can remains sealed tight. The
|
||
physicist devises a complex system of wheels and pulleys to pop the top off
|
||
the can. This crude machine unfortunately fails as well. After watching the
|
||
lack of success of his fellow strandees, the economist announces that he has
|
||
the solution: “Assume we have a can opener.”
|
||
In the spirit of economists’ logic, let’s imagine for a moment a theoretical
|
||
economic microcosm in which a trader has two trading accounts at the same
|
||
firm. The assumptions here are that a trader can borrow 100 percent of a
|
||
stock’s value to finance the purchase of the security and that there are no
|
||
legal, moral, or other limitations on trading. In one account the trader is
|
||
long 100 shares, fully leveraged. In the other, the trader is short 100 shares
|
||
of the same stock, in which case the trader earns a short-stock rebate.
|
||
In the long run, what is the net result of this trade? Most likely, this trade
|
||
is a losing proposition for the trader, because the interest rate at which the
|
||
trader borrows capital is likely to be higher than the interest rate earned on
|
||
the short-stock proceeds. In this example, interest is the main consideration.
|
||
But interest matters in the real world, too. Professional traders earn
|
||
interest on proceeds from short stock and pay interest on funds borrowed.
|
||
Interest rates may vary slightly from firm to firm and trader to trader.
|
||
Interest rates are personal. The interest rate a trader should use when pricing
|
||
options is specific to his or her situation.
|
||
A trader with no position in a particular stock who is interested in trading
|
||
a conversion should consider that he will be buying the stock. This implies
|
||
borrowing funds to open the long stock position. The trader should price his
|
||
options according to the rate he will pay to borrow funds. Conversely, a
|
||
trader trading a reversal should consider the fact that he is shorting the stock
|
||
and will receive interest at the rate of the short-stock rebate. This trader
|
||
should price his options at the short-stock rate.
|
||
A Call Is a Put
|
||
The idea that “a put is a call, a call is a put” is an important one, indeed. It
|
||
lays the foundation for more advanced spreading strategies. The concepts in
|
||
this chapter in one way or another enter into every spread strategy that will
|
||
be discussed in this book from here on out.
|
||
Note
|
||
1 . Note, for simplicity, simple interest is used in the computation.
|
||
CHAPTER 7
|
||
Rho
|
||
Interest is one of the six inputs of an option-pricing model for American
|
||
options. Although interest rates can remain constant for long periods, when
|
||
interest rates do change, call and put values can be positively or negatively
|
||
affected. Some options are more sensitive to changes in the interest rate
|
||
than others. To the unaware trader, interest-rate changes can lead to
|
||
unexpected profits or losses. But interest rates don’t have to be a wild-card
|
||
risk. They’re one that experienced traders watch closely to avoid
|
||
unnecessary risk and increase profitability. To monitor the effect of changes
|
||
in the interest rate, it is important to understand the quiet greek—rho.
|
||
Rho and Interest Rates
|
||
Rho is a measurement of the sensitivity of an option’s value to a change in
|
||
the interest rate. To understand how and why the interest rate is important to
|
||
the value of an option, recall the formula for put-call parity stated in
|
||
Chapter 6.
|
||
Call + Strike − Interest = Put + Stock 1
|
||
From this formula, it’s clear that as the interest rate rises, put prices must
|
||
fall and call prices must rise to keep put-call parity balanced. With a little
|
||
algebra, the equation can be restated to better illustrate this concept:
|
||
and
|
||
If interest rates fall,
|
||
and
|
||
Rho helps quantify this relationship. Calls have positive rho, and puts
|
||
have negative rho. For example, a call with a rho of +0.08 will gain $0.08
|
||
with each one-percentage-point rise in interest rates and fall $0.08 with
|
||
each one-percentage-point fall in interest rates. A put with a rho of −0.08
|
||
will lose $0.08 with each one-point rise and gain $0.08 in value with a one-
|
||
point fall.
|
||
The effect of changes in the interest variable of put-call parity on call and
|
||
put values is contingent on three factors: the strike price, the interest rate,
|
||
and the number of days until expiration.
|
||
Interest = Strike×Interest Rate×(Days to Expiration/365) 2
|
||
Interest, for our purposes, is a function of the strike price. The higher the
|
||
strike price, the greater the interest and, consequently the more changes in
|
||
the interest rate will affect the option. The higher the interest rate is, the
|
||
higher the interest variable will be. Likewise, the more time to expiration,
|
||
the greater the effect of interest. Rho measures an option’s sensitivity to the
|
||
end results of these three influences.
|
||
To understand how changes in interest affect option prices, consider a
|
||
typical at-the-money (ATM) conversion on a non-dividend-paying stock.
|
||
Short 1 May 50 call at 1.92
|
||
Long 1 May 50 put at 1.63
|
||
Long 100 shares at $50
|
||
With 43 days until expiration at a 5 percent interest rate, the interest on
|
||
the 50 strike will be about $0.29. Put-call parity ensures that this $0.29
|
||
shows up in option prices. After rearranging the equation, we get
|
||
In this example, both options are exactly ATM. There is no intrinsic value.
|
||
Therefore, the difference between the extrinsic values of the call and the put
|
||
must equal interest. If one option were in-the-money (ITM), the intrinsic
|
||
value on the left side of the equation would be offset by the Stock − Strike
|
||
on the right side. Still, it would be the difference in the time value of the
|
||
call and put that equals the interest variable.
|
||
This is shown by the fact that the synthetic stock portion of the
|
||
conversion is short at $50.29 (call − put + strike). This is $0.29 above the
|
||
stock price. The synthetic stock equals the Stock + Interest, or
|
||
Certainly, if the interest rate were higher, the interest on the synthetic
|
||
stock would be a higher number. At a 6 percent interest rate, the effective
|
||
short price of the synthetic stock would be about $50.35. The call would be
|
||
valued at about 1.95, and the put would be 1.60—a net of $0.35.
|
||
A one-percentage-point rise in the interest rate causes the synthetic stock
|
||
position to be revalued by $0.06—a $0.03 gain in the call value and a $0.03
|
||
decline in the put. Therefore, by definition, the call has a +0.03 rho and the
|
||
put has a −0.03 rho.
|
||
Rho and Time
|
||
The time component of interest has a big impact on the magnitude of an
|
||
option’s rho, because the greater the number of days until expiration, the
|
||
greater the interest. Long-term options will be more sensitive to changes in
|
||
the interest rate and, therefore, have a higher rho.
|
||
Take a stock trading at about $120 per share. The July, October, and
|
||
January ATM calls have the following rhos with the interest rate at 5.5
|
||
percent.
|
||
Option Rho
|
||
July (38-day) 120 calls+0.068
|
||
October (130-day) 120 calls+0.226
|
||
January (221-day) 120 calls+0.385
|
||
If interest rates rise 25 basis points, or a quarter of a percentage point, the
|
||
July calls with only 38 days until expiration will gain very little: only
|
||
$0.017 (0.068 × 0.25). The October 120 calls with 130 days until expiration
|
||
gain more: $0.057 (0.226 × 0.25). The January calls that have 221 days
|
||
until they expire make $0.096 theoretically (0.385 × 0.25). If all else is held
|
||
constant, the more time to expiration, the higher the option’s rho, and
|
||
therefore, the more interest will affect the option’s value.
|
||
Considering Rho When Planning
|
||
Trades
|
||
Just having an opinion on a stock is only half the battle in options trading.
|
||
Choosing the best way to trade a forecast can make all the difference to the
|
||
success of a trade. Options give traders choices. And one of the choices a
|
||
trader has is the month in which to trade. When trading LEAPS—Long-
|
||
Term Equity AnticiPation Securities—delta, gamma, theta, and vega are
|
||
important, as always, but rho is also a valuable part of the strategy.
|
||
LEAPS
|
||
Options buyers have time working against them. With each passing day,
|
||
theta erodes the value of their assets. Buying a long-term option, or a
|
||
LEAPS, helps combat erosion because long-term options can decay at a
|
||
slower rate. In environments where there is interest rate uncertainty,
|
||
however, LEAPS traders have to think about more than the rate of decay.
|
||
Consider two traders: Jason and Susanne. Both are bullish on XYZ Corp.
|
||
(XYZ), which is trading at $59.95 per share. Jason decides to buy a May 60
|
||
call at 1.60, and Susanne buys a LEAPS 60 call at 7.60. In this example,
|
||
May options have 44 days until expiration, and the LEAPS have 639 days.
|
||
Both of these trades are bullish, but the traders most likely had slightly
|
||
different ideas about time, volatility, and interest rates when they decided
|
||
which option to buy. Exhibit 7.1 compares XYZ short-term at-the-money
|
||
calls with XYZ LEAPS ATM calls.
|
||
EXHIBIT 7.1 XYZ short-term call vs. LEAPS call.
|
||
To begin with, it appears that Susanne was allowing quite a bit of time for
|
||
her forecast to be realized—almost two years. Jason, however, was looking
|
||
for short-term price appreciation. Concerns about time decay may have
|
||
been a motivation for Susanne to choose a long-term option—her theta of
|
||
0.01 is half Jason’s, which is 0.02. With only 44 days until expiration, the
|
||
theta of Jason’s May call will begin to rise sharply as expiration draws near.
|
||
But the trade-off of lower time decay is lower gamma. At the current
|
||
stock price, Susanne has a higher delta. If the XYZ stock price rises $2, the
|
||
gamma of the May call will cause Jason’s delta to creep higher than
|
||
Susanne’s. At $62, the delta for the May 60s would be about 0.78, whereas
|
||
the LEAPS 60 call delta is about 0.77. This disparity continues as XYZ
|
||
moves higher.
|
||
Perhaps Susanne had implied volatility (IV) on her mind as well as time
|
||
decay. These long-term ATM LEAPS options have vegas more than three
|
||
times the corresponding May’s. If IV for both the May and the LEAPS is at
|
||
a yearly low, LEAPS might be a better buy. A one- or two-point rise in
|
||
volatility if IV reverts to its normal level will benefit the LEAPS call much
|
||
more than the May.
|
||
Theta, delta, gamma, and vega are typical considerations with most
|
||
trades. Because this option is long term, in addition to these typical
|
||
considerations, Susanne needs to take a good hard look at rho. The LEAPS
|
||
rho is significantly higher than that of its short-term counterpart. A one-
|
||
percentage-point change in the interest rate will change Susanne’s P&(L) by
|
||
$0.64—that’s about 8.5 percent of the value of her option—and she has
|
||
nearly two years of exposure to interest rate fluctuations. Certainly, when
|
||
the Federal Reserve Board has great concerns about growth or inflation,
|
||
rates can rise or fall by more than one percentage point in one year’s time.
|
||
It is important to understand that, like the other greeks, rho is a snapshot
|
||
at a particular price, volatility level, interest rate, and moment in time. If
|
||
interest rates were to fall by one percentage point today, it would cause
|
||
Susanne’s call to decline in value by $0.64. If that rate drop occurred over
|
||
the life of the option, it would have a much smaller effect. Why? Rate
|
||
changes closer to expiration have less of an effect on option values.
|
||
Assume that on the trade date, when the LEAPS has 639 days until
|
||
expiration, interest rates fall by 25 basis points. The effect will be a decline
|
||
in the value of the call of 0.16—one-fourth of the 0.638 rho. If the next rate
|
||
cut occurs six months later, the rho of the LEAPS will be smaller, because it
|
||
will have less time until expiration. In this case, after six months, the rho
|
||
will be only 0.46. Another 25-basis-point drop will hurt the call by $0.115.
|
||
After another six months, the option will have a 0.26 rho. Another quarter-
|
||
point cut costs Susanne only $0.065. Any subsequent rate cuts in ensuing
|
||
months will have almost no effect on the now short-term option value.
|
||
Pricing in Interest Rate Moves
|
||
In the same way that volatility can get priced in to an option’s value, so can
|
||
the interest rate. When interest rates are expected to rise or fall, those
|
||
expectations can be reflected in the prices of options. Say current interest
|
||
rates are at 8 percent, but the Fed has announced that the economy is
|
||
growing at too fast of a pace and that it may raise interest rates at the next
|
||
Federal Open Market Committee meeting. Analysts expect more rate hikes
|
||
to follow. The options with expiration dates falling after the date of the
|
||
expected rate hikes will have higher interest rates priced in. In this situation,
|
||
the higher interest rates in the longer-dated options will be evident when
|
||
entering parameters into the model.
|
||
Take options on Already Been Chewed Bubblegum Corp. (ABC). A
|
||
trader, Kyle, enters parameters into the model for ABC options and notices
|
||
that the prices don’t line up. To get the theoretical values of the ATM calls
|
||
for all the expiration months to sit in the middle of the actual market values,
|
||
Kyle may have to tinker with the interest rate inputs.
|
||
Assume the following markets for the ATM 70-strike calls in ABC
|
||
options:
|
||
Calls Puts
|
||
Aug 70 calls1.75–1.851.30–1.40
|
||
Sep 70 calls2.65–2.751.75–1.85
|
||
Dec 70 calls4.70–4.902.35–2.45
|
||
Mar 70 calls6.50–6.702.65–2.75
|
||
ABC is at $70 a share, has a 20 percent IV in all months, and pays no
|
||
dividend. August expiration is one month away.
|
||
Entering the known inputs for strike price, stock price, time to expiration,
|
||
volatility, and dividend and using an 8 percent interest rate yields the
|
||
following theoretical values for ABC options:
|
||
The theoretical values, in bold type, are those that don’t line up in the
|
||
middle of the call and put markets. These values are wrong. The call
|
||
theoretical values are too low, and the put theoretical values are too high.
|
||
They are the product of an interest rate that is too low being applied to the
|
||
model. To generate values that are indicative of market prices, Kyle must
|
||
change the interest input to the pricing model to reflect the market’s
|
||
expectations of future interest rate changes.
|
||
Using new values for the interest rate yields the following new values:
|
||
After recalculating, the theoretical values line up in the middle of the call
|
||
and put markets. Using higher interest rates for the longer expirations raises
|
||
the call values and lowers the put values for these months. These interest
|
||
rates were inferred from, or backed out of, the option-market prices by use
|
||
of the option-pricing model. In practice, it may take some trial and error to
|
||
find the correct interest values to use.
|
||
In times of interest rate uncertainty, rho can be an important factor in
|
||
determining which strategy to select. When rates are generally expected to
|
||
continue to rise or fall over time, they are normally priced in to the options,
|
||
as shown in the previous example. When there is no consensus among
|
||
analysts and traders, the rates that are priced in may change as economic
|
||
data are made available. This can cause a revision of option values. In long-
|
||
term options that have higher rhos, this is a bona fide risk. Short-term
|
||
options are a safer play in this environment. But as all traders know, risk
|
||
also implies opportunity.
|
||
Trading Rho
|
||
While it’s possible to trade rho, most traders forgo this niche for more
|
||
dynamic strategies with greater profitability. The effects of rho are often
|
||
overshadowed by the more profound effects of the other greeks. The
|
||
opportunity to profit from rho is outweighed by other risks. For most
|
||
traders, rho is hardly ever even looked at.
|
||
Because LEAPS have higher rho values than corresponding short-term
|
||
options, it makes sense that these instruments would be appropriate for
|
||
interest-rate plays. But even with LEAPS, rho exposure usually pales in
|
||
comparison with that of delta, theta, and vega.
|
||
It is not uncommon for the rho of a long-term option to be 5 to 8 percent
|
||
of the option’s value. For example, Exhibit 7.2 shows a two-year LEAPS on
|
||
a $70 stock with the following pricing-model inputs and outputs:
|
||
EXHIBIT 7.2 Long 70-strike LEAPS call.
|
||
The rho is +0.793, or about 5.8 percent of the call value. That means a 25-
|
||
basis-point rise in rates contributes to only a 20-cent profit on the call.
|
||
That’s only about 1.5 percent of the call’s value. On one hand, 1.5 percent is
|
||
not a very big profit on a trade. On the other hand, if there are more rate
|
||
rises at following Fed meetings, the trader can expect further gains on rho.
|
||
Even if the trader is compelled to wait until the next Fed meeting to make
|
||
another $0.20—or less, as rho will get smaller as time passes—from a
|
||
second 25-basis-point rate increase, other influences will diminish rho’s
|
||
significance. If over the six-week period between Fed meetings, the
|
||
underlying declines by just $0.60, the $0.40 that the trader hoped to make
|
||
on rho is wiped out by delta loss. With the share price $0.60 lower, the
|
||
0.760 delta costs the trade about $0.46. Furthermore, the passing of six
|
||
weeks (42 days) will lead to a loss of about $0.55 from time decay because
|
||
of the −0.013 theta. There is also the risk from the fat vegas associated with
|
||
LEAPS. A 1.5 percent drop in implied volatility completely negates any
|
||
hopes of rho profits.
|
||
Aside from the possibility that delta, theta, and vega may get in the way
|
||
of profits, the bid-ask spread with these long-term options tends to be wider
|
||
than with their short-term counterparts. If the bid-ask spread is more than
|
||
$0.40 wide, which is often the case with LEAPS, rho profits are canceled
|
||
out by this cost of doing business. Buying the offer and selling the bid
|
||
negative scalps away potential profits.
|
||
With LEAPS, rho is always a concern. It will contribute to prosperity or
|
||
peril and needs to be part of the trade plan from forecast to implementation.
|
||
Buying or selling a LEAPS call or put, however, is not a practical way to
|
||
speculate on interest rates.
|
||
To take a position on interest rates in the options market, risk needs to be
|
||
distilled down to rho. The other greeks need to be spread off. This is
|
||
accomplished only through the conversions, reversals, and jelly rolls
|
||
described in Chapter 6. However, the bid-ask can still be a hurdle to trading
|
||
these strategies for non–market makers. Generally, rho is a greek that for
|
||
most traders is important to understand but not practical to trade.
|
||
Notes
|
||
1 . Please note, for simplification, dividends are not included.
|
||
2 . Note, for simplicity, simple interest is used in the calculation.
|
||
CHAPTER 8
|
||
Dividends and Option Pricing
|
||
Much of this book studies how to break down and trade certain components
|
||
of option prices. This chapter examines the role of dividends in the pricing
|
||
structure. There is no greek symbol that measures an option’s sensitivity to
|
||
changes in the dividend. And in most cases, dividends are not “traded” by
|
||
means of options in the same way that volatility, interest, and other option
|
||
price influences are. Dividends do, though, affect option prices, and
|
||
therefore a trader’s P&(L), so they deserve attention.
|
||
There are some instances where dividends provide ample opportunity to
|
||
the option trader, and there some instances where a change in dividend
|
||
policy can have desirable, or undesirable, effects on the bottom line.
|
||
Despite the fact that dividends do not technically involve greeks, they need
|
||
to be monitored in much the same way as do delta, gamma, theta, vega, and
|
||
rho.
|
||
Dividend Basics
|
||
Let’s start at the beginning. When a company decides to pay a dividend,
|
||
there are four important dates the trader must be aware of:
|
||
1. Declaration date
|
||
2. Ex-dividend date
|
||
3. Record date
|
||
4. Payable date
|
||
The first date chronologically is the declaration date. This date is when
|
||
the company formally declares the dividend. It’s when the company lets its
|
||
shareholders know when and in what amount it will pay the dividend.
|
||
Active traders, however, may buy and sell the same stock over and over
|
||
again. How does the corporation know exactly who collects the dividend
|
||
when it is opening up its coffers?
|
||
Dividends are paid to shareholders of record who are on the company’s
|
||
books as owning the stock at the opening of business on another important
|
||
date: the record date. Anyone long the stock at this moment is entitled to the
|
||
dividend. Anyone with a short stock position on the opening bell on the
|
||
record date is required to make payment in the amount of the dividend.
|
||
Because the process of stock settlement takes time, the important date is
|
||
actually not the record date. For all intents and purposes, the key date is two
|
||
days before the record date. This is called the ex-dividend date, or the ex-
|
||
date.
|
||
Traders who have earned a dividend by holding a stock in their account
|
||
on the morning of the ex-date have one more important date they need to
|
||
know—the date they get paid. The date that the dividend is actually paid is
|
||
called the payable date. The payable date can be a few weeks after the ex-
|
||
date.
|
||
Let’s walk through an example. ABC Corporation announces on March
|
||
21 (the declaration date) that it will pay a 25-cent dividend to shareholders
|
||
of record on April 3 (the record date), payable on April 23 (the payable
|
||
date). This means market participants wishing to receive the dividend must
|
||
own the stock on the open on April 1 (the ex-date). In practice, they must
|
||
buy the stock before the closing bell rings on March 31 in order to have it
|
||
for the open the next day.
|
||
This presents a potential quandary. If a trader only needs to have the stock
|
||
on the open on the ex-date, why not buy the stock just before the close on
|
||
the day before the ex-date, in this case March 31, and sell it the next
|
||
morning after the open? Could this be an opportunity for riskless profit?
|
||
Unfortunately, no. There are a couple of problems with that strategy. First,
|
||
as far as the riskless part is concerned, stock prices can and often do change
|
||
overnight. Yesterday’s close and today’s open can sometimes be
|
||
significantly different. When they are, it is referred to as a gap open.
|
||
Whenever a stock is held (long or short), there is risk. The second problem
|
||
with this strategy to earn riskless profit is with the profit part. On the ex-
|
||
date, the opening stock price reflects the dividend. Say ABC is trading at
|
||
$50 at the close on March 31. If the market for the stock opens unchanged
|
||
the next morning—that is, a zero net change on the day on—ABC will be
|
||
trading at $49.75 ($50 minus the $0.25 dividend). Alas, the quest for
|
||
riskless profit continues.
|
||
Dividends and Option Pricing
|
||
The preceding discussion demonstrated how dividends affect stock traders.
|
||
There’s one problem: we’re option traders! Option holders or writers do not
|
||
receive or pay dividends, but that doesn’t mean dividends aren’t relevant to
|
||
the pricing of these securities. Observe the behavior of a conversion or a
|
||
reversal before and after an ex-dividend date. Assuming the stock opens
|
||
unchanged on the ex-date, the relationship of the price of the synthetic stock
|
||
to the actual stock price will change. Let’s look at an example to explore
|
||
why.
|
||
At the close on the day before the ex-date of a stock paying a $0.25
|
||
dividend, a trader has an at-the-money (ATM) conversion. The stock is
|
||
trading right at $50 per share. The 50 puts are worth 2.34, and the 50 calls
|
||
are worth 2.48. Before the ex-date, the trader is
|
||
Long 100 shares at $50
|
||
Long one 50 put at 2.34
|
||
Short one 50 call at 2.48
|
||
Here, the trader is long the stock at $50 and short stock synthetically at
|
||
$50.14—50 + (2.48 − 2.34). The trader is synthetically short $0.14 over the
|
||
price at which he is long the stock.
|
||
Assume that the next morning the stock opens unchanged. Since this is
|
||
the ex-date, that means the stock opens at $49.75—$0.25 lower than the
|
||
previous day’s close. The theoretical values of the options will change very
|
||
little. The options will be something like 2.32 for the put and 2.46 for the
|
||
call.
|
||
After the ex-date, the trader is
|
||
Long 100 shares at $49.75
|
||
Long one 50 put at 2.32
|
||
Short one 50 call at 2.46
|
||
Each option is two cents lower. Why? The change in the option prices is
|
||
due to theta. In this case, it’s $0.02 for each option. The synthetic stock is
|
||
still short from an effective price of $50.14. With the stock at $49.75, the
|
||
synthetic short price is now $0.39 over the stock. Incidentally, $0.39 is
|
||
$0.25 more than the $0.14 difference before the ex-date.
|
||
Did the trader who held the conversion overnight from before the ex-date
|
||
to after it make or lose money? Neither. Before the ex-date, he had an asset
|
||
worth $50 per share (the stock) and he shorted the asset synthetically at
|
||
$50.14. After the ex-date, he still has assets totaling $50 per share—the
|
||
stock at $49.75 plus the 0.25 dividend—and he is still synthetically short
|
||
the stock at $50.14. Before the ex-date, the $0.14 difference between the
|
||
synthetic and the stock is interest minus the dividend. After the ex-date, the
|
||
$0.39 difference is all interest.
|
||
Dividends and Early Exercise
|
||
As the ex-date approaches, in-the-money (ITM) calls on equity options can
|
||
often be found trading at parity, regardless of the dividend amount and
|
||
regardless of how far off expiration is. This seems counterintuitive. What
|
||
about interest? What about dividends? Normally, these come into play in
|
||
option valuation.
|
||
But option models designed for American options take the possibility of
|
||
early exercise into account. It is possible to exercise American-style calls
|
||
and exchange them for the underlying stock. This would give traders, now
|
||
stockholders, the right to the dividend—a right for which they would not be
|
||
eligible as call holders. Because of the impending dividend, the call
|
||
becomes an exercise just before the ex-date. For this reason, the call can
|
||
trade for parity before the ex-date.
|
||
Let’s look at an example of a reversal on a $70 stock that pays a $0.40
|
||
dividend. The options in this reversal have 24 days until expiration, which
|
||
makes the interest on the 60 strike roughly $0.20, given a 5 percent interest
|
||
rate. The day before the ex-date, a trader has the following position at the
|
||
stated prices:
|
||
Short 100 shares at $70
|
||
Long one 60 call at 10.00
|
||
Short one 60 put at 0.05
|
||
To understand how American calls work just before the ex-date, it is
|
||
helpful first to consider what happens if the trader holds the position until
|
||
the ex-date. Making the assumption that the stock is unchanged on the ex-
|
||
dividend date, it will open at $69.60, lower by the amount of the dividend—
|
||
in this case, $0.40. The put, being so far out-of-the-money (OTM) as to
|
||
have a negligible delta, will remain unchanged. But what about the call?
|
||
With no dividend left in the stock, the put call-parity states
|
||
In this case,
|
||
|
||
Before the ex-date, the model valued the call at parity. Now it values the
|
||
same call at $0.25 over parity (9.85 − [69.60 − 60]). Another way to look at
|
||
this is that the time value of the call is now made up of the interest plus the
|
||
put premium. Either way, that’s a gain of $0.25 on the call. That sounds
|
||
good, but because the trader is short stock, if he hasn’t exercised, he will
|
||
owe the $0.40 dividend—a net loss of $0.15. The new position will be
|
||
Short 100 shares at $69.60
|
||
Owe $0.40 dividend
|
||
Long one 60 call at 9.85
|
||
Short one 60 put at 0.05
|
||
At the end of the trading day before the ex-date, this trader must exercise
|
||
the call to capture the dividend. By doing so, he closes two legs of the trade
|
||
—the call and the stock. The $10 call premium is forfeited, the stock that is
|
||
short at $70 is bought at $60 (from the call exercise) for a $10 profit. The
|
||
transaction leads to neither a profit nor a loss. The purpose of exercising is
|
||
to avoid the $0.15 loss ($0.25 gain in call time value minus the $0.40 loss in
|
||
dividends owed).
|
||
The other way the trader could achieve the same ends is to sell the long
|
||
call and buy in the short stock. This is tactically undesirable because the
|
||
trader may have to sell the bid in the call and buy the offer in the stock.
|
||
Furthermore, when legging a trade in this manner, there is the risk of
|
||
slippage. If the call is sold first, the stock can move before the trader has a
|
||
chance to buy it at the necessary price. It is generally better and less risky to
|
||
exercise the call rather than leg out of the trade.
|
||
In this transaction, the trader begins with a fairly flat position (short
|
||
stock/long synthetic stock) and ends with a short put that is significantly
|
||
out-of-the-money. For all intents and purposes, exercising the call in this
|
||
trade is like synthetically selling the put. But at what price? In this case, it’s
|
||
$0.15. This again is the cost benefit of saving $0.40 by avoiding the
|
||
dividend obligation versus the $0.25 gain in call time value. Exercising the
|
||
call is effectively like selling the put at 0.15 in this example. If the dividend
|
||
is lower or the interest is higher, it may not be worth it to the trader to
|
||
exercise the call to capture the dividend. How do traders know if their calls
|
||
should be exercised?
|
||
The traders must do the math before each ex-dividend date in option
|
||
classes they trade. The traders have to determine if the benefit from
|
||
exercising—or the price at which the synthetic put is essentially being sold
|
||
—is more or less than the price at which they can sell the put. The math
|
||
used here is adopted from put-call parity:
|
||
This shows the case where the traders can effectively synthetically sell the
|
||
put (by exercising) for more than the current put value. Tactically, it’s
|
||
appropriate to use the bid price for the put in this calculation since that is
|
||
the price at which the put can be sold.
|
||
In this case, the traders would be inclined to not exercise. It would be
|
||
theoretically more beneficial to sell the put if the trader is so inclined.
|
||
Here, the traders, from a valuation perspective, are indifferent as to whether
|
||
or not to exercise. The question then is simply: do they want to sell the put
|
||
at this price?
|
||
Professionals and big retail traders who are long (ITM) calls—whether as
|
||
part of a reversal, part of another type of spread, or because they are long
|
||
the calls outright—must do this math the day before each ex-dividend date
|
||
to maximize profits and minimize losses. Not exercising, or forgetting to
|
||
exercise, can be a costly mistake. Traders who are short ITM dividend-
|
||
paying calls, however, can reap the benefits of those sleeping on the job. It
|
||
works both ways.
|
||
Traders who are long stock and short calls at parity before the ex-date
|
||
may stand to benefit if some of the calls do not get assigned. Any shares of
|
||
long stock remaining on the ex-date will result in the traders receiving
|
||
dividends. If the dividends that will be received are greater in value than the
|
||
interest that will subsequently be paid on the long stock, the traders may
|
||
stand reap an arbitrage profit because of long call holders’ forgetting to
|
||
exercise.
|
||
Dividend Plays
|
||
The day before an ex-dividend date in a stock, option volume can be
|
||
unusually high. Tens of thousands of contracts sometimes trade in names
|
||
that usually have average daily volumes of only a couple thousand. This
|
||
spike in volume often has nothing to do with the market’s opinion on
|
||
direction after the dividend. The heavy trading has to do with the
|
||
revaluation of the relationship of exercisable options to the underlying
|
||
expected to occur on the ex-dividend date.
|
||
Traders that are long ITM calls and short ITM calls at another strike just
|
||
before an ex-dividend date have a potential liability and a potential benefit.
|
||
The potential liability is that they can forget to exercise. This is a liability
|
||
over which the traders have complete control. The potential benefit is that
|
||
some of the short calls may not get assigned. If traders on the other side of
|
||
the short calls (the longs) forget to exercise, the traders that are short the
|
||
call make out by not having to pay the dividend on short stock.
|
||
Professionals and big retail traders who have very low transaction costs
|
||
will sometimes trade ITM call spreads during the afternoon before an ex-
|
||
dividend date. This consists of buying one call and selling another call with
|
||
a different strike price. Both calls in the dividend-play strategy are ITM and
|
||
have corresponding puts with little or no value (to be sure, the put value is
|
||
less than the dividend minus the interest). The traders trade the spreads,
|
||
fairly indifferent as to whether they buy or sell the spreads, in hope of
|
||
skating—or not getting assigned—on some of their short calls. The more
|
||
they don’t get assigned the better.
|
||
This usually occurs in options that have high open interest, meaning there
|
||
are a lot of outstanding contracts already. The more contracts in existence,
|
||
the better the possibility of someone forgetting to exercise. The greatest
|
||
volume also tends to occur in the front month.
|
||
Strange Deltas
|
||
Because American calls become an exercise possibility when the ex-date is
|
||
imminent, the deltas can sometimes look odd. When the calls are trading at
|
||
parity, they have a 1.00 delta. They are a substitute for the stock. They, in
|
||
fact, will be stock if and when they are exercised just before the ex-date.
|
||
But if the puts still have some residual time value, they may also have a
|
||
small delta, of 0.05 or perhaps more.
|
||
In this unique scenario, the delta of the synthetic can be greater than
|
||
+1.00 or less than −1.00. It is not uncommon to see the absolute values of
|
||
the call and put deltas add up to 1.07 or 1.08. When the dividend comes out
|
||
of the options model on the ex-date, synthetics go back to normal. The delta
|
||
of the synthetic again approaches 1.00. Because of the out-of-whack deltas,
|
||
delta-neutral traders need to take extra caution in their analytics when ex-
|
||
dates are near. A little common sense should override what the computer
|
||
spits out.
|
||
Inputting Dividend Data into the
|
||
Pricing Model
|
||
Often dividend payments are regular and predictable. With many
|
||
companies, the dividend remains constant quarter after quarter. Some
|
||
corporations have a track record of incrementally increasing their dividends
|
||
every year. Some companies pay dividends in a very irregular fashion, by
|
||
paying special dividends that are often announced as a surprise to investors.
|
||
In a truly capitalist society, there are no restrictions and no rules on when,
|
||
whether, or how corporations pay dividends to their shareholders.
|
||
Unpredictability of dividends, though, can create problems in options
|
||
valuation.
|
||
When a company has a constant, reasonably predictable dividend, there is
|
||
not a lot of guesswork. Take Exelon Corp. (EXC). From November 2008 to
|
||
the time of this writing, Exelon has paid a regular quarterly dividend of
|
||
$0.525. During that period, a trader has needed simply to enter 0.525 into
|
||
the pricing calculator for all expected future dividends to generate the
|
||
theoretical value. Based on recent past performance, the trader could feel
|
||
confident that the computed analytics were reasonably accurate. If the
|
||
trader believed the company would continue its current dividend policy,
|
||
there would be little options-related dividend risk—unless things changed.
|
||
When there is uncertainty about when future dividends will be paid in
|
||
what amounts, the level of dividend-related risk begins to increase. The
|
||
more uncertainty, the more risk. Let’s examine an interesting case study:
|
||
General Electric (GE).
|
||
For a long time, GE was a company that has had a history of increasing
|
||
its dividends at fairly regular intervals. In fact, there was more than a 30-
|
||
year stretch in which GE increased its dividend every year. During most of
|
||
the first decade of the 2000s, increases in GE’s dividend payments were
|
||
around one to six cents and tended to occur toward the end of December,
|
||
after December expiration. The dividends were paid four times per year but
|
||
not exactly quarterly. For several years, the ex-dates were in February, June,
|
||
September, and December. Option traders trading GE options had a pretty
|
||
easy time estimating their future dividend streams, and consequently
|
||
evaded valuation problems that could result from using wrong dividend
|
||
data. Traders would simply adjust the dividend data in the model to match
|
||
their expectations for predictably increasing future dividends in order to
|
||
achieve an accurate theoretical value. Let’s look back at GE to see how a
|
||
trader might have done this.
|
||
The following shows dividend-history data for GE.
|
||
Ex-DateDividend*
|
||
12/27/02$0.19
|
||
02/26/03$0.19
|
||
06/26/03$0.19
|
||
09/25/03$0.19
|
||
12/29/03$0.20
|
||
02/26/04$0.20
|
||
06/24/04$0.20
|
||
09/23/04$0.20
|
||
12/22/04$0.22
|
||
02/24/05$0.22
|
||
06/23/05$0.22
|
||
09/22/05$0.22
|
||
12/22/05$0.25
|
||
02/23/06$0.25
|
||
06/22/06$0.25
|
||
09/21/06$0.25
|
||
12/21/06$0.28
|
||
02/22/07$0.28
|
||
06/21/07$0.28
|
||
* These data are taken from the following Web page on GE’s web site:
|
||
www.ge.com/investors/stock_info/dividend_history.html .
|
||
At the end of 2006, GE raised its dividend from $0.25 to $0.28. A trader
|
||
trading GE options at the beginning of 2007 would have logically
|
||
anticipated the next increase to occur again in the following December
|
||
unless there was reason to believe otherwise. Options expiring before this
|
||
anticipated next dividend increase would have the $0.28 dividend priced
|
||
into their values. Options expiring after December 2007 would have a
|
||
higher dividend priced into them—possibly an additional three cents to 0.31
|
||
(which indeed it was). Calls would be adversely affected by this increase,
|
||
and puts would be favorably affected. A typical trader would have
|
||
anticipated those changes. The dividend data a trader pricing GE options
|
||
would have entered into the model in January 2007 would have looked
|
||
something like this.
|
||
Ex-DateDividend*
|
||
02/22/07$0.28
|
||
06/21/07$0.28
|
||
09/20/07$0.28
|
||
12/20/07$0.31
|
||
02/21/08$0.31
|
||
06/19/08$0.31
|
||
09/18/08$0.31
|
||
* These data are taken from the following Web page on GE’s web site:
|
||
www.ge.com/investors/stock_info/dividend_history.html .
|
||
The trader would have entered the anticipated future dividend amount in
|
||
conjunction with the anticipated ex-dividend date. This trader projection
|
||
goes out to February 2008, which would aid in valuing options expiring in
|
||
2007 as well as the 2008 LEAPS. Because the declaration dates had yet to
|
||
occur, one could not know with certainty when the dividends would be
|
||
announced or in what amount. Certainly, there would be some estimation
|
||
involved for both the dates and the amount. But traders would probably get
|
||
it pretty close—close enough.
|
||
Then, something particularly interesting happened. Instead of raising the
|
||
dividend going into December 2008 as would be a normal pattern, GE kept
|
||
it the same. As shown, the 12/24/08 ex-dated dividend remained $0.31.
|
||
Ex-DateDividend*
|
||
02/22/07$0.28
|
||
06/21/07$0.28
|
||
09/20/07$0.28
|
||
12/20/07$0.31
|
||
02/21/08$0.31
|
||
06/19/08$0.31
|
||
09/18/08$0.31
|
||
12/24/08$0.31
|
||
* These data are taken from the following Web page on GE’s web site:
|
||
www.ge.com/investors/stock_info/dividend_history.html .
|
||
The dividend stayed at $0.31 until the June 2009 dividend, which held
|
||
another jolt for traders pricing options. Around this time, GE’s stock price
|
||
had taken a beating. It fell from around $42 a share in the fall of 2007
|
||
ultimately to about $6 in March 2009. GE had its first dividend cut in more
|
||
than three decades. The dividend with the ex-date of 06/18/09 was $0.10.
|
||
12/24/08$0.31
|
||
02/19/09$0.31
|
||
06/18/09$0.10
|
||
09/17/09$0.10
|
||
12/23/09$0.10
|
||
02/25/10$0.10
|
||
06/17/10$0.10
|
||
09/16/10$0.12
|
||
12/22/10$0.14
|
||
02/24/11$0.14
|
||
06/16/11$0.15
|
||
09/15/11$0.15
|
||
Though the company gave warnings in advance, the drastic dividend
|
||
change had a significant impact on option prices. Call prices were helped by
|
||
the dividend cut (or anticipated dividend cut) and put prices were hurt.
|
||
The break in the pattern didn’t stop there. The dividend policy remained
|
||
$0.10 for five quarters until it rose to $0.12 in September 2010, then to
|
||
$0.14 in December 2010, then to $0.15 in June 2011. These irregular
|
||
changes in the historically predictable dividend policy made it tougher for
|
||
traders to attain accurate valuations. If the incremental changes were bigger,
|
||
the problem would have been even greater.
|
||
Good and Bad Dates with Models
|
||
Using an incorrect date for the ex-date in option pricing can lead to
|
||
unfavorable results. If the ex-dividend date is not known because it has yet
|
||
to be declared, it must be estimated and adjusted as need be after it is
|
||
formally announced. Traders note past dividend history and estimate the
|
||
expected dividend stream accordingly. Once the dividend is declared, the
|
||
ex-date is known and can be entered properly into the pricing model. Not
|
||
executing due diligence to find correct known ex-dates can lead to trouble.
|
||
Using a bad date in the model can yield dubious theoretical values that can
|
||
be misleading or worse—especially around the expiration.
|
||
Say a call is trading at 2.30 the day before the ex-date of a $0.25
|
||
dividend, which happens to be thirty days before expiration. The next day,
|
||
of course, the stock may have moved higher or lower. Assume for
|
||
illustrative purposes, to compare apples to apples as it were, that the stock is
|
||
trading at the same price—in this case, $76.
|
||
If the trader is using the correct date in the model, the option value will
|
||
adjust to take into account the effect of the dividend expiring, or reaching
|
||
its ex-date, when the number of days to expiration left changes from 30 to
|
||
29. The call trading postdividend will be worth more relative to the same
|
||
stock price. If the dividend date the trader is using in the model is wrong,
|
||
say one day later than it should be, the dividend will still be an input of the
|
||
theoretical value. The calculated value will be too low. It will be wrong.
|
||
Exhibit 8.1 compares the values of a 30-day call on the ex-date given the
|
||
right and the wrong dividend.
|
||
EXHIBIT 8.1 Comparison of 30-day call values
|
||
At the same stock price of $76 per share, the call is worth $0.13 more
|
||
after the dividend is taken out of the valuation. Barring any changes in
|
||
implied volatility (IV) or the interest rate, the market prices of the options
|
||
should reflect this change. A trader using an ex-date in the model that is
|
||
farther in the future than the actual ex-date will still have the dividend as
|
||
part of the generated theoretical value. With the ex-date just one day later,
|
||
the call would be worth 2.27. The difference in option value is due to the
|
||
effect of theta—in this case, $0.03.
|
||
With a bad date, the value of 2.27 would likely be significantly below
|
||
market price, causing the market value of the option to look more expensive
|
||
than it actually is. If the trader did not know the date was wrong, he would
|
||
need to raise IV to make the theoretical value match the market. This option
|
||
has a vega of 0.08, which translates into a difference of about two IV points
|
||
for the theoretical values 2.43 and 2.27. The trader would perceive the call
|
||
to be trading at an IV two points higher than the market indicates.
|
||
Dividend Size
|
||
It’s not just the date but also the size of the dividend that matters. When
|
||
companies change the amount of the dividend, options prices follow in step.
|
||
In 2004, when Microsoft (MSFT) paid a special dividend of $3 per share,
|
||
there were unexpected winners and losers in the Microsoft options. Traders
|
||
who were long calls or short puts were adversely affected by this change in
|
||
dividend policy. Traders with short calls or long puts benefited. With long-
|
||
term options, even less anomalous changes in the size of the dividend can
|
||
have dramatic effects on options values.
|
||
Let’s study an example of how an unexpected rise in the quarterly
|
||
dividend of a stock affects a long call position. Extremely Yellow Zebra
|
||
Corp. (XYZ) has been paying a quarterly dividend of $0.10. After a steady
|
||
rise in stock price to $61 per share, XYZ declares a dividend payment of
|
||
$0.50. It is expected that the company will continue to pay $0.50 per
|
||
quarter. A trader, James, owns the 528-day 60-strike calls, which were
|
||
trading at 9.80 before the dividend increase was announced.
|
||
Exhibit 8.2 compares the values of the long-term call using a $0.10
|
||
quarterly dividend and using a $0.50 quarterly dividend.
|
||
EXHIBIT 8.2 Effect of change in quarterly dividend on call value.
|
||
This $0.40 dividend increase will have a big effect on James’s calls. With
|
||
528 days until expiration, there will be six dividends involved. Because
|
||
James is long the calls, he loses 1.52 per option. If, however, he were short
|
||
the calls, 1.52 would be his profit on each option.
|
||
Put traders are affected as well. Another trader, Marty, is long the 60-
|
||
strike XYZ puts. Before the dividend announcement, Marty was running his
|
||
values with a $0.10 dividend, giving his puts a value of 5.42. Exhibit 8.3
|
||
compares the values of the puts with a $0.10 quarterly dividend and with a
|
||
$0.50 quarterly dividend.
|
||
EXHIBIT 8.3 Effect of change in quarterly dividend on put value.
|
||
When the dividend increase is announced, Marty will benefit. His puts
|
||
will rise because of the higher dividend by $0.66 (all other parameters held
|
||
constant). His long-term puts with six quarters of future expected dividends
|
||
will benefit more than short-term XYZ puts of the same strike would. Of
|
||
course, if he were short the puts, he would lose this amount.
|
||
The dividend inputs to a pricing model are best guesses until the dates
|
||
and amounts are announced by the company. How does one find dividend
|
||
information? Regularly monitoring the news and press releases on the
|
||
companies one trades is a good way to stay up to date on dividend
|
||
information, as well as other company news. Dividend announcements are
|
||
widely disseminated by the major news services. Most companies also have
|
||
an investor-relations phone number and section on their web sites where
|
||
dividend information can be found.
|
||
PART II
|
||
Spreads
|
||
CHAPTER 9
|
||
Vertical Spreads
|
||
Risk—it is the focal point around which all trading revolves. It may seem as
|
||
if profit should be occupying this seat, as most important to trading options,
|
||
but without risk, there would be no profit! As traders, we must always look
|
||
for ways to mitigate, eliminate, preempt, and simply avoid as much risk as
|
||
possible in our pursuit of success without diluting opportunity. Risk must be
|
||
controlled. Trading vertical spreads takes us one step further in this quest.
|
||
The basic strategies discussed in Chapters 4 and 5 have strengths when
|
||
compared with pure linear trading in the equity markets. But they have
|
||
weaknesses, too. Consider the covered call, one of the most popular option
|
||
strategies.
|
||
A covered call is best used as an augmentation to an investment plan. It
|
||
can be used to generate income on an investment holding, as an entrance
|
||
strategy into a stock, or as an exit strategy out of a stock. But from a trading
|
||
perspective, one can often find better ways to trade such a forecast.
|
||
If the forecast on a stock is neutral to moderately bullish, accepting the
|
||
risk of stock ownership is often unwise. There is always the chance that the
|
||
stock could collapse. In many cases, this is an unreasonable risk to assume.
|
||
To some extent, we can make the same case for the long call, short put,
|
||
naked call, and the like. In certain scenarios, each of these basic strategies is
|
||
accompanied with unwanted risks that serve no beneficial purpose to the
|
||
trader but can potentially cause harm. In many situations, a vertical spread
|
||
is a better alternative to these basic spreads. Vertical spreads allow a trader
|
||
to limit potential directional risk, limit theta and vega risk, free up margin,
|
||
and generally manage capital more efficiently.
|
||
Vertical Spreads
|
||
Vertical spreads involve buying one option and selling another. Both are on
|
||
the same underlying and expire the same month, and both are either calls or
|
||
puts. The difference is in the strike prices of the two options. One is higher
|
||
than the other, hence the name vertical spread . There are four vertical
|
||
spreads: bull call spread, bear call spread, bear put spread, and bull put
|
||
spread. These four spreads can be sliced and diced into categories a number
|
||
of ways: call spreads and put spreads, bull spreads and bear spreads, debit
|
||
spreads and credit spreads. There is overlap among the four verticals in how
|
||
and when they are used. The end of this chapter will discuss how the
|
||
spreads are interrelated.
|
||
Bull Call Spread
|
||
A bull call spread is a long call combined with a short call that has a higher
|
||
strike price. Both calls are on the same underlying and share the same
|
||
expiration month. Because the purchased call has a lower strike price, it
|
||
costs more than the call being sold. Establishing the trade results in a debit
|
||
to the trader’s account. Because of this debit, it’s called a debit spread.
|
||
Below is an example of a bull call spread on Apple Inc. (AAPL):
|
||
In this example, Apple is trading around $391. With 40 days until
|
||
February expiration, the trader buys the 395–405 call spread for a net debit
|
||
of $4.40, or $440 in actual cash. Or one could simply say the trader paid
|
||
$4.40 for the 395–405 call.
|
||
Consider the possible outcomes if the spread is held until expiration.
|
||
Exhibit 9.1 shows an at-expiration diagram of the bull call spread.
|
||
EXHIBIT 9.1 AAPL bull call spread.
|
||
Before discussing the greeks, consider the bull call spread from an at-
|
||
expiration perspective. Unlike the long call, which has two possible
|
||
outcomes at expiration—above or below the strike—this spread has three
|
||
possibilities: below both strikes, between the strikes, or above both strikes.
|
||
In this example, if Apple is below $395 at expiration, both calls expire
|
||
worthless. The rights and obligations of the options are gone, as is the cash
|
||
spent on the trade. In this case, the entire debit of $4.40 is lost.
|
||
If Apple is between the strikes at expiration, the 405-strike call expires
|
||
worthless. The trader is long stock at an effective price of $399.40. This is
|
||
the $395-strike price at which the stock would be purchased if the call is
|
||
exercised, plus the $4.40 premium spent on the spread. The break-even
|
||
price of the trade is $399.40. If Apple is above $399.40 at expiration, the
|
||
trade is profitable; below $399.40, it is a loser. The aptly named bull call
|
||
spread requires the stock to rise to reach its profit potential. But unlike an
|
||
outright long call, profits are capped with the spread.
|
||
If Apple is above $405 at expiration, both calls are in-the-money (ITM).
|
||
If the 395-strike calls are exercised, the trader buys 100 shares of Apple at
|
||
$395 and these shares, in turn, would be sold at $405 when the 405-strike
|
||
calls are assigned, for a $10 gain per share. Subtract from that $10 the $4.40
|
||
debit spent on the trade and the net profit is $5.60 per share.
|
||
There are some other differences between the 395–405 call spread and the
|
||
outright purchase of the 395 call. The absolute risk is lower. To buy the
|
||
395-strike call costs 14.60, versus 4.40 for the spread—a big difference.
|
||
Because the debit is lower, the margin for the spread is lower at most
|
||
option-friendly brokers, as well.
|
||
If we dig a little deeper, we find some other differences between the bull
|
||
call spread and the outright call. Long options are haunted by the specter of
|
||
time. Because the spread involves both a long and a short option, the time-
|
||
decay risk is lower than that associated with owning an option outright.
|
||
Implied volatility (IV) risk is lower, too. Exhibit 9.2 compares the greeks of
|
||
the long 395 call with those of the 395–405 call spread.
|
||
EXHIBIT 9.2 Apple call versus bull call spread (Apple @ $391).
|
||
395 Call395–405 Call
|
||
Delta 0.484 0.100
|
||
Gamma0.00970.0001
|
||
Theta −0.208−0.014
|
||
Vega 0.513 0.020
|
||
The positive deltas indicate that both positions are bullish, but the outright
|
||
call has a higher delta. Some of the 395 call’s directional sensitivity is lost
|
||
when the 405 call is sold to make a spread. The negative delta of the 405
|
||
call somewhat offsets the positive delta of the 395 call. The spread delta is
|
||
only about 20 percent of the outright call’s delta. But for a trader wanting to
|
||
focus on trading direction, the smaller delta can be a small sacrifice for the
|
||
benefit of significantly reduced theta and vega. Theta spread’s risk is about
|
||
7 percent that of the outright. The spread’s vega risk is also less than 4
|
||
percent that of the outright 395 call. With the bull call spread, a trader can
|
||
spread off much of the exposure to the unwanted risks and maintain a
|
||
disproportionately higher greeks in the wanted exposure (delta).
|
||
These relationships change as the underlying moves higher. Remember,
|
||
at-the-money (ATM) options have the greatest sensitivity to theta and vega.
|
||
With Apple sitting at around the long strike, gamma and vega have their
|
||
greatest positive value, and theta has its most negative value. Exhibit 9.3
|
||
shows the spread greeks given other underlying prices.
|
||
EXHIBIT 9.3 AAPL 395–405 bull call spread.
|
||
As the stock moves higher toward the 405 strike, the 395 call begins to
|
||
move away from being at-the-money, and the 405 call moves toward being
|
||
at-the-money. The at-the-money is the dominant strike when it comes to the
|
||
characteristics of the spread greeks. Note the greeks position when the
|
||
underlying is directly between the two strike prices: The long call has
|
||
ceased to be the dominant influence on these metrics. Both calls influence
|
||
the analytics pretty evenly. The time-decay risk has been entirely spread off.
|
||
The volatility risk is mostly spread off. Gamma remains a minimal concern.
|
||
When the greeks of the two calls balance each other, the result is a
|
||
directional play.
|
||
As AAPL continues to move closer to the 405-strike, it becomes the at-
|
||
the-money option, with the dominant greeks. The gamma, theta, and vega
|
||
of the 405 call outweigh those of the ITM 395 call. Vega is more negative.
|
||
Positive theta now benefits the trade. The net gamma of the spread has
|
||
turned negative. Because of the negative gamma, the delta has become
|
||
smaller than it was when the stock was at $400. This means that the benefit
|
||
of subsequent upward moves in the stock begins to wane. Recall that there
|
||
is a maximum profit threshold with a vertical spread. As the stock rises
|
||
beyond $405, negative gamma makes the delta smaller and time decay
|
||
becomes less beneficial. But at this point, the delta has done its work for the
|
||
trader who bought this spread when the stock was trading around $395. The
|
||
average delta on a move in the stock from $395 to $405 is about 0.10 in this
|
||
case.
|
||
When the stock is at the 405 strike, the characteristics of the trade are
|
||
much different than they are when the stock is at the 395 strike. Instead of
|
||
needing movement upward in the direction of the delta to combat the time
|
||
decay of the long calls, the position can now sit tight at the short strike and
|
||
reap the benefits of option decay. The key with this spread, and with all
|
||
vertical spreads, is that the stock needs to move in the direction of the delta
|
||
to the short strike.
|
||
Strengths and Limitations
|
||
There are many instances when a bull call spread is superior to other bullish
|
||
strategies, such as a long call, and there are times when it isn’t. Traders
|
||
must consider both price and time.
|
||
A bull call spread will always be cheaper than the outright call purchase.
|
||
That’s because the cost of the long-call portion of the spread is partially
|
||
offset by the premium of the higher-strike short call. Spending less for the
|
||
same exposure is always a better choice, but the exposure of the vertical is
|
||
not exactly the same as that of the long call. The most obvious trade-off is
|
||
the fact that profit is limited. For smaller moves—up to the price of the
|
||
short strike—vertical spreads tend to be better trades than outright call
|
||
purchases. Beyond the strike? Not so much.
|
||
But time is a trade-off, too. There have been countless times that I have
|
||
talked with new traders who bought a call because they thought the stock
|
||
was going up. They were right and still lost money. As the adage goes,
|
||
timing is everything. The more time that passes, the more advantageous the
|
||
lower-theta vertical spread becomes. When held until expiration, a vertical
|
||
spread can be a better trade than an outright call in terms of percentage
|
||
profit.
|
||
In the previous example, when Apple is at $391 with 40 days until
|
||
expiration, the 395 call is worth 14.60 and the spread is worth 4.40. If
|
||
Apple were to rise to be trading at $405 at expiration, the call rises to be
|
||
worth 10, for a loss of 4.60 on the 14.60 debit paid. The spread also is worth
|
||
10. It yields a gain of about 127 percent on the initial $4.40 per share debit.
|
||
But look at this same trade if the move occurs before expiration. If Apple
|
||
rallies to $405 after only a couple weeks, the outcome is much different.
|
||
With four weeks still left until expiration, the 395 call is worth 19.85 with
|
||
the underlying at $405. That’s a 36 percent gain on the 14.60. The spread is
|
||
worth 5.70. That’s a 30 percent gain. The vertical spread must be held until
|
||
expiration to reap the full benefits, which it accomplishes through erosion
|
||
of the short option.
|
||
The long-call-only play (with a significantly larger negative theta) is
|
||
punished severely by time passing. The long call benefits more from a
|
||
quick move in the underlying. And of course, if the stock were to rise to a
|
||
price greater than $405, in a short amount of time—the best of both worlds
|
||
for the outright call—the outright long 395 call would be emphatically
|
||
superior to the spread.
|
||
Bear Call Spread
|
||
The next type of vertical spread is called a bear call spread . A bear call
|
||
spread is a short call combined with a long call that has a higher strike
|
||
price. Both calls are on the same underlying and share the same expiration
|
||
month. In this case, the call being sold is the option of higher value. This
|
||
call spread results in a net credit when the trade is put on and, therefore, is
|
||
called a credit spread.
|
||
The bull call spread and the bear call spread are two sides of the same
|
||
coin. The difference is that with the bull call spread, one is buying the call
|
||
spread, and with the bear call spread, one is selling the call spread. An
|
||
example of a bear call spread can be shown using the same trade used
|
||
earlier.
|
||
Here we are selling one AAPL February (40-day) 395 call at 14.60 and
|
||
buying the 405 call at 10.20. We are selling the 395–405 call at $4.40 per
|
||
share, or $440.
|
||
Exhibit 9.4 is an at-expiration diagram of the trade.
|
||
EXHIBIT 9.4 Apple bear call spread.
|
||
The same three at-expiration outcomes are possible here as with the bull
|
||
call spread: the stock can be above both strikes, between both strikes, or
|
||
below both strikes. If the stock is below both strikes at expiration, both calls
|
||
will expire worthless. The rights and obligations cease to exist. In this case,
|
||
the entire credit of $440 is profit.
|
||
If AAPL is between the two strike prices at expiration, the 395-strike call
|
||
will be in-the-money. The short call will get assigned and result in a short
|
||
stock position at expiration. The break-even price falls at $399.40—the
|
||
short strike plus the $4.40 net premium. This is the price at which the stock
|
||
will effectively be sold if assignment occurs.
|
||
If Apple is above both strikes at expiration, it means both calls are in-the-
|
||
money. Stock is sold at $395 because of assignment and bought back at
|
||
$405 through exercise. This leads to a loss of $10 per share on the negative
|
||
scalp. Factoring in the $4.40-per-share credit makes the net loss only $5.60
|
||
per share with AAPL above $405 at February expiration.
|
||
Just as the at-expiration diagram is the same but reversed, the greeks for
|
||
this call spread will be similar to those in the bull call spread example
|
||
except for the positive and negative signs. See Exhibit 9.5 .
|
||
EXHIBIT 9.5 Apple 395–405 bear call spread.
|
||
A credit spread is commonly traded as an income-generating strategy. The
|
||
idea is simple: sell the option closer-to-the-money and buy the more out-of-
|
||
the-money (OTM) option—that is, sell volatility—and profit from
|
||
nonmovement (above a certain point). In this example, with Apple at $391,
|
||
a neutral to slightly bearish trader would think about selling this spread at
|
||
4.40 in hopes that the stock will remain below $395 until expiration. The
|
||
best-case scenario is that the stock is below $395 at expiration and both
|
||
options expire, resulting in a $4.40-per-share profit.
|
||
The strategy profits as long as Apple is under its break-even price,
|
||
$399.40, at expiration. But this is not so much a bearish strategy as it is a
|
||
nonbullish strategy. The maximum gain with a credit spread is the premium
|
||
received, in this case $4.40 per share. Traders who thought AAPL was
|
||
going to decline sharply would short it or buy a put. If they thought it would
|
||
rise sharply, they’d use another strategy.
|
||
From a greek perspective, when the trade is executed it’s very close to its
|
||
highest theta price point—the 395 short strike price. This position
|
||
theoretically collects $0.90 a day with Apple at around $395. As time
|
||
passes, that theta rises. The key is that the stock remains at around $395
|
||
until the short option is just about worthless. The name of the game is sit
|
||
and wait.
|
||
Although the delta is negative, traders trading this spread to generate
|
||
income want the spread to expire worthless so they can pocket the $4.40 per
|
||
share. If Apple declines, profits will be made on delta, and theta profits will
|
||
be foregone later. All that matters is the break-even point. Essentially, the
|
||
idea is to sell a naked call with a maximum potential loss. Sell the 395s and
|
||
buy the 405s for protection.
|
||
If the underlying decreases enough in the short term and significant
|
||
profits from delta materialize, it is logical to consider closing the spread
|
||
early. But it often makes more sense to close part of the spread. Consider
|
||
that the 405-strike call is farther out-of-the-money and will lose its value
|
||
before the 395 call.
|
||
Say that after two weeks a big downward move occurs. Apple is trading at
|
||
$325 a share; the 405s are 0.05 bid at 0.10, and the 395s are 0.50 bid at
|
||
0.55. At this point, the lion’s share of the profits can be taken early. A trader
|
||
can do so by closing only the 395 calls. Closing the 395s to eliminate the
|
||
risk of negative delta and gamma makes sense. But does it make sense to
|
||
close the 405s for 0.05? Usually not. Recouping this residual value
|
||
accomplishes little. It makes more sense to leave them in your position in
|
||
case the stock rebounds. If the stock proves it can move down $70; it can
|
||
certainly move up $70. Because the majority of the profits were taken on
|
||
the 395 calls, holding on to the 405s is like getting paid to own calls. In
|
||
scenarios where a big move occurs and most of the profits can be taken
|
||
early, it’s often best to hold the long calls, just in case. It’s a win-win
|
||
situation.
|
||
Credit and Debit Spread Similarities
|
||
The credit call spread and the debit call spread appear to be exactly opposite
|
||
in every respect. Many novice traders perceive credit spreads to be
|
||
fundamentally different from debit spreads. That is not necessarily so.
|
||
Closer study reveals that these two are not so different after all.
|
||
What if Apple’s stock price was higher when the trade was put on? What
|
||
if the stock was at $405? First, the spread would have had more value. The
|
||
395 and 405 calls would both be worth more. A trader could have sold the
|
||
spread for a $5.65-per-share credit. The at-expiration diagram would look
|
||
almost the same. See Exhibit 9.6 .
|
||
EXHIBIT 9.6 Apple bear call spread initiated with Apple at $405.
|
||
Because the net premium is much higher in this example, the maximum
|
||
gain is more—it is $5.65 per share. The breakeven is $400.65. The price
|
||
points on the at-expiration diagram, however, have nothing to do with the
|
||
greeks. The analytics from Exhibit 9.5 are the same either way.
|
||
The motivation for a trader selling this call spread, which has both
|
||
options in-the-money, is different from that for the typical income
|
||
generator. When the spread is sold in this context, the trader is buying
|
||
volatility. Long gamma, long vega, negative theta. The trader here has a
|
||
trade more like the one in the bull call spread example—except that instead
|
||
of needing a rally, the trader needs a rout. The only difference is that the
|
||
bull call spread has a bullish delta, and the bear call spread has a bearish
|
||
delta.
|
||
Bear Put Spread
|
||
There is another way to take a bearish stance with vertical spreads: the bear
|
||
put spread. A bear put spread is a long put plus a short put that has a lower
|
||
strike price. Both puts are on the same underlying and share the same
|
||
expiration month. This spread, however, is a debit spread because the more
|
||
expensive option is being purchased.
|
||
Imagine that a stock has had a good run-up in price. The chart shows a
|
||
steady march higher over the past couple of months. A study of technical
|
||
analysis, though, shows that the run-up may be pausing for breath. An
|
||
oscillator, such as slow stochastics, in combination with the relative
|
||
strength index (RSI), indicates that the stock is overbought. At the same
|
||
time, the average directional movement index (ADX) confirms that the
|
||
uptrend is slowing.
|
||
For traders looking for a small pullback, a bear put spread can be an
|
||
excellent strategy. The goal is to see the stock drift down to the short strike.
|
||
So, like the other members of the vertical spread family, strike selection is
|
||
important.
|
||
Let’s look at an example of ExxonMobil (XOM). After the stock has
|
||
rallied over a two-month period to $80.55, a trader believes there will be a
|
||
short-term temporary pullback to $75. Instead of buying the June 80 puts
|
||
for 1.75, the trader can buy the 75–80 put spread of the same month for
|
||
1.30 because the 75 put can be sold for 0.45. 1
|
||
In this example, the June put has 40 days until expiration. Exhibit 9.7
|
||
illustrates the payout at expiration.
|
||
EXHIBIT 9.7 ExxonMobil bear put spread.
|
||
If the trader is wrong and ExxonMobil is still above 80 at expiry, both
|
||
puts expire and the 1.30 premium is lost. If ExxonMobil is between the two
|
||
strikes, the 80 puts are ITM, resulting in an exercise, and the 75 puts are
|
||
OTM and expire. The net effect is short stock at an effective price of
|
||
$78.70. The effective sale price is found by taking the price at which the
|
||
short stock is established when the puts are exercised—$80—minus the net
|
||
1.30 paid for the spread. This is the spread’s breakeven at expiration.
|
||
If the trader is right and ExxonMobil is below both strikes at expiration,
|
||
both puts are ITM, and the result is a 3.70 profit and no position. Why a
|
||
3.70 profit? The 80 puts are exercised, making the trader short at $80, and
|
||
the 75 puts are assigned, so the short is bought back at $75 for a positive
|
||
stock scalp of $5. Including the 1.30 debit for the spread in the profit and
|
||
loss (P&(L)), the net profit is $3.70 per share when the stock is below both
|
||
strikes at expiration.
|
||
This is a bearish trade. But is the bear put spread necessarily a better trade
|
||
than buying an outright ATM put? No. The at-expiration diagram makes this
|
||
clear. Profits are limited to $3.70 per share. This is an important difference.
|
||
But because in this particular example, the trader expects the stock to
|
||
retrace only to around $75, the benefits of lower cost and lower theta and
|
||
vega risk can be well worth the trade-off of limited profit. The trader’s
|
||
objectives are met more efficiently by buying the spread. The goal is to
|
||
profit from the delta move down from $80 to $75. Exhibit 9.8 shows the
|
||
differences between the greeks of the outright put and the spread when the
|
||
trade is put on with ExxonMobil at $80.55.
|
||
EXHIBIT 9.8 ExxonMobil put vs. bear put spread (ExxonMobil @
|
||
$80.55).
|
||
80 Put75–80 Put
|
||
Delta −0.445−0.300
|
||
Gamma+0.080+0.041
|
||
Theta −0.018−0.006
|
||
Vega +0.110+0.046
|
||
As in the call-spread examples discussed previously, the spread delta is
|
||
smaller than the outright put’s. It appears ironic that the spread with the
|
||
smaller delta is a better trade in this situation, considering that the intent is
|
||
to profit from direction. But it is the relative differences in the greeks
|
||
besides delta that make the spread worthwhile given the trader’s goal.
|
||
Gamma, theta, and vega are proportionately much smaller than the delta in
|
||
the spread than in the outright put. While the spread’s delta is two thirds
|
||
that of the put, its gamma is half, its theta one third, and its vega around 42
|
||
percent of the put’s.
|
||
Retracements such as the one called for by the trader in this example can
|
||
happen fast, sometimes over the course of a week or two. It’s not
|
||
necessarily bad if this move occurs quickly. If ExxonMobil drops by $5
|
||
right away, the short delta will make the position profitable. Exhibit 9.9
|
||
shows how the spread position changes as the stock declines from $80 to
|
||
$75.
|
||
EXHIBIT 9.9 75–80 bear put spread as ExxonMobil declines.
|
||
|
||
The delta of this trade remains negative throughout the stock’s descent to
|
||
$75. Assuming the $5 drop occurs in one day, a delta averaging around
|
||
−0.36 means about a 1.80 profit, or $180 per spread, for the $5 move (0.36
|
||
times $5 times 100). This is still a far cry from the spread’s $3.70 potential
|
||
profit. Although the stock is at $75, the maximum profit potential has yet to
|
||
be reached, and it won’t be until expiration. How does the rest of the profit
|
||
materialize? Time decay.
|
||
The price the trader wants the stock to reach is $75, but the assumption
|
||
here is that the move happens very fast. The trade went from being a long-
|
||
volatility play—long gamma and vega—to a short-vol play: short gamma
|
||
and vega. The trader wanted movement when the stock was at $80 and
|
||
wants no movement when the stock is at $75. When the trade changes
|
||
characteristics by moving from one strike to another, the trader has to
|
||
reconsider the stock’s outlook. The question is: if I didn’t have this position
|
||
on, would I want it now?
|
||
The trader has a choice to make: take the $180 profit—which represents a
|
||
138 percent profit on the 1.30 debit—or wait for theta to do its thing. The
|
||
trader looking for a retracement would likely be inclined to take a profit on
|
||
the trade. Nobody ever went broke taking a profit. But if the trader thinks
|
||
the stock will sit tight for the remaining time until expiration, he will be
|
||
happy with this income-generating position.
|
||
Although the trade in the last, overly simplistic example did not reap its
|
||
full at-expiration potential, it was by no means a bad trade. Holding the
|
||
spread until expiration is not likely to be part of a trader’s plan. Buying the
|
||
80 put outright may be a better play if the trader is expecting a fast move. It
|
||
would have a bigger delta than the spread. Debit and credit spreads can be
|
||
used as either income generators or as delta plays. When they’re used as
|
||
delta plays, however, time must be factored in.
|
||
Bull Put Spread
|
||
The last of the four vertical spreads is a bull put spread. A bull put spread is
|
||
a short put with one strike and a long put with a lower strike. Both puts are
|
||
on the same underlying and in the same expiration cycle. A bull put spread
|
||
is a credit spread because the more expensive option is being sold, resulting
|
||
in a net credit when the position is established. Using the same options as in
|
||
the bear put example:
|
||
With ExxonMobil at $80.55, the June 80 puts are sold for 1.75 and the
|
||
June 75 puts are bought at 0.45. The trade is done for a credit of 1.30.
|
||
Exhibit 9.10 shows the payout of this spread if it is held until expiration.
|
||
EXHIBIT 9.10 ExxonMobil bull put spread.
|
||
The sale of this spread generates a 1.30 net credit, which is represented by
|
||
the maximum profit to the right of the 80 strike. With ExxonMobil above
|
||
$80 per share at expiration, both options expire OTM and the premium is
|
||
all profit. Between the two strike prices, the 80 put expires in the money. If
|
||
the ITM put is still held at expiration, it will be assigned. Upon assignment,
|
||
the put becomes long stock, profiting with each tick higher up to $80, or
|
||
losing with each tick lower to $75. If the 80 put is assigned, the effective
|
||
price of the long stock will be $78.70. The assignment will “hit your sheets”
|
||
as a buy at $80, but the 1.30 credit lowers the effective net cost to $78.70.
|
||
If the stock is below $75 at option expiration, both puts will be ITM. This
|
||
is the worst case scenario, because the higher-struck put was sold. At
|
||
expiration, the 80 puts would be assigned, the 75 puts exercised. That’s a
|
||
negative scalp of $5 on the resulting stock. The initial credit lessens the pain
|
||
by 1.30. The maximum possible loss with ExxonMobil below both strikes
|
||
at expiration is $3.70 per spread.
|
||
The spread in this example is the flip side of the bear put spread of the
|
||
previous example. Instead of buying the spread, as with the bear put, the
|
||
spread in this case is sold.
|
||
Exhibit 9.11 shows the analytics for the bull put spread.
|
||
EXHIBIT 9.11 Greeks for ExxonMobil 75–80 bull put spread.
|
||
Instead of having a short delta, as with the bear spread, the bull spread is
|
||
long delta. There is negative theta with positive gamma and vega as XOM
|
||
approaches the long strike—the 75s, in this case. There is also positive theta
|
||
with negative gamma and vega around the short strike—the 80s.
|
||
Exhibit 9.11 shows the characteristics that define the vertical spread. If
|
||
one didn’t know which particular options were being traded here, this could
|
||
almost be a table of greeks for either a 75–80 bull put spread or a 75–80
|
||
bull call spread.
|
||
Like the other three verticals, this spread can be a delta play or a theta
|
||
play. A bullish trader may sell the spread if both puts are in-the-money.
|
||
Imagine that XOM is trading at around $75. The spread will have a positive
|
||
0.364 delta, positive gamma, and negative theta. The spread as a whole is a
|
||
decaying asset. It needs the underlying to rally to combat time decay.
|
||
A bullish trader may also sell this spread if XOM is between the two
|
||
strikes. In this case, with XOM at, say, $77, the delta is +0.388, and all
|
||
other greeks are negligible. At this particular price point in the underlying,
|
||
the trader has almost pure leveraged delta exposure. But this trade would be
|
||
positioned for only a small move, not much above $80. A speculator
|
||
wanting to trade direction for a small move while eliminating theta and
|
||
vega risks achieves her objectives very well with a vertical spread.
|
||
A bullish-to-neutral trader would be inclined to sell this spread if
|
||
ExxonMobil were around $80 or higher. Day by day, the 1.30 premium
|
||
would start to come in. With 40 days until expiration, theta would be small,
|
||
only 0.004. But if the stock remained at $80, this ATM put would begin
|
||
decaying faster and faster. The objective of trading this spread for a neutral
|
||
trader is selling future realized volatility—selling gamma to earn theta. A
|
||
trader can also trade a vertical spread to profit from IV.
|
||
Verticals and Volatility
|
||
The IV component of a vertical spread, although small compared with that
|
||
of an outright call or put, is still important—especially for large traders with
|
||
low margin and low commissions who can capitalize on small price
|
||
changes efficiently. Whether it’s a call spread or a put spread, a credit
|
||
spread or a debit spread, if the underlying is at the short option’s strike, the
|
||
spread will have a net negative vega. If the underlying is at the long
|
||
option’s strike, the spread will have positive vega. Because of this
|
||
characteristic, there are three possible volatility plays with vertical spreads:
|
||
speculating on IV changes when the underlying remains constant, profiting
|
||
from IV changes resulting from movement of the underlying, and special
|
||
volatility situations.
|
||
Vertical spreads offer a limited-risk way to speculate on volatility changes
|
||
when the underlying remains fairly constant. But when the intent of a
|
||
vertical spread is to benefit from vega, one must always consider the delta
|
||
—it’s the bigger risk. Chapter 13 discusses ways to manage this risk by
|
||
hedging with stock, a strategy called delta-neutral trading.
|
||
Non-delta-neutral traders may speculate on vol with vertical spreads by
|
||
assuming some delta risk. Traders whose forecast is vega bearish will sell
|
||
the option with the strike closest to where the underlying is trading—that is,
|
||
the ATM option—and buy an OTM strike. Traders would lean with their
|
||
directional bias by choosing either a call spread or a put spread. As risk
|
||
managers, the traders balance the volatility stance being taken against the
|
||
additional risk of delta. Again, in this scenario, delta can hurt much more
|
||
than help.
|
||
In the ExxonMobil bull put spread example, the trader would sell the 80-
|
||
strike put if ExxonMobil were around $80 a share. In this case, if the stock
|
||
didn’t move as time passed, theta would benefit from historical volatility
|
||
being’s low—that is, from little stock movement. At first, the benefit would
|
||
be only 0.004 per day, speeding up as expiration nears. And if implied
|
||
volatility decreased, the trader would profit 0.04 for every 1 percent decline
|
||
in IV. Small directional moves upward help a little. But in the long run,
|
||
those profits are leveled off by the fact that theta gets smaller as the stock
|
||
moves higher above $80—more profit on direction, less on time.
|
||
For the delta player, bull call spreads and bull put spreads have a potential
|
||
added benefit that stems from the fact that IV tends to decrease as stocks
|
||
rise and increase when stocks fall. This offers additional opportunity to the
|
||
bull spread player. With the bull call spread or the bull put spread, the trader
|
||
gains on positive delta with a rally. Once the underlying comes close to the
|
||
short option’s strike, vega is negative. If IV declines, as might be
|
||
anticipated, there is a further benefit of vega profits on top of delta profits.
|
||
If the underlying declines, the trader loses on delta. But the pain can
|
||
potentially be slightly lessened by vega profits. Vega will get positive as the
|
||
underlying approaches the long strike, which will benefit from the firming
|
||
of IV that often occurs when the stock drops. But this dual benefit is paid
|
||
for in the volatility skew. In most stocks or indexes, the lower strikes—the
|
||
ones being bought in a bull spread—have higher IVs than the higher strikes,
|
||
which are being sold.
|
||
Then there are special market situations in which vertical spreads that
|
||
benefit from volatility changes can be traded. Traders can trade vertical
|
||
spreads to strategically position themselves for an expected volatility
|
||
change. One example of such a situation is when a stock is rumored to be a
|
||
takeover target. A natural instinct is to consider buying calls as an
|
||
inexpensive speculation on a jump in price if the takeover is announced.
|
||
Unfortunately, the IV of the call is often already bid up by others with the
|
||
same idea who were quicker on the draw. Buying a call spread consisting of
|
||
a long ITM call and a short OTM call can eliminate immediate vega risk
|
||
and still provide wanted directional exposure.
|
||
Certainly, with this type of trade, the trader risks being wrong in terms of
|
||
direction, time, and volatility. If and when a takeover bid is announced, it
|
||
will likely be for a specific price. In this event, the stock price is unlikely to
|
||
rise above the announced takeover price until either the deal is
|
||
consummated or a second suitor steps in and offers a higher price to buy the
|
||
company. If the takeover is a “cash deal,” meaning the acquiring company
|
||
is tendering cash to buy the shares, the stock will usually sit in a very tight
|
||
range below the takeover price for a long time. In this event, implied
|
||
volatility will often drop to very low levels. Being short an ATM call when
|
||
the stock rallies will let the trader profit from collapsing IV through
|
||
negative vega.
|
||
Say XYZ stock, trading at $52 a share, is a rumored takeover target at
|
||
$60. When the rumors are first announced, the stock will likely rise, to say
|
||
$55, with IV rising as well. Buying the 50–60 call spread will give a trader
|
||
a positive delta and a negligible vega. If the rumors are realized and a cash
|
||
takeover deal is announced at $60, the trade gains on delta, and the spread
|
||
will now have negative vega. The negative vega at the 60 strike gains on
|
||
implied volatility declining, and the stock will sit close to $60, producing
|
||
the benefits of positive theta. Win, win, win.
|
||
The Interrelations of Credit
|
||
Spreads and Debit Spreads
|
||
Many traders I know specialize in certain niches. Sometimes this is because
|
||
they find something they know well and are really good at. Sometimes it’s
|
||
because they have become comfortable and don’t have the desire to try
|
||
anything new. I’ve seen this strategy specialization sometimes with traders
|
||
trading credit spreads and debit spreads. I’ve had serial credit spread traders
|
||
tell me credit spreads are the best trades in the world, much better than debit
|
||
spreads. Habitual debit spread traders have likewise said their chosen
|
||
spread is the best. But credit spreads and debit spreads are not so different.
|
||
In fact, one could argue that they are really the same thing.
|
||
Conventionally, credit-spread traders have the goal of generating income.
|
||
The short option is usually ATM or OTM. The long option is more OTM.
|
||
The traders profit from nonmovement via time decay. Debit-spread traders
|
||
conventionally are delta-bet traders. They buy the ATM or just out-of-the-
|
||
money option and look for movement away from or through the long strike
|
||
to the short strike. The common themes between the two are that the
|
||
underlying needs to end up around the short strike price and that time has to
|
||
pass to get the most out of either spread.
|
||
With either spread, movement in the underlying may be required,
|
||
depending on the relationship of the underlying price to the strike prices of
|
||
the options. And certainly, with a credit spread or debit spread, if the
|
||
underlying is at the short strike, that option will have the most premium.
|
||
For the trade to reach the maximum profit, it will need to decay.
|
||
For many retail traders, debit spreads and credit spreads begin to look
|
||
even more similar when margin is considered. Margin requirements can
|
||
vary from firm to firm, but verticals in retail accounts at option-friendly
|
||
brokerage firms are usually margined in such a way that the maximum loss
|
||
is required to be deposited to hold the position (this assumes Regulation T
|
||
margining). For all intents and purposes, this can turn the trader’s cash
|
||
position from a credit into a debit. From a cash perspective, all vertical
|
||
spreads are spreads that require a debit under these margin requirements.
|
||
Professional traders and retail traders who are subject to portfolio margining
|
||
are subject to more liberal margin rules.
|
||
Although margin is an important concern, what we really care about as
|
||
traders is risk versus reward. A credit call spread and a debit put spread on
|
||
the same underlying, with the same expiration month, sharing the same
|
||
strike prices will also share the same theoretical risk profile. This is because
|
||
call and put prices are bound together by put-call parity.
|
||
Building a Box
|
||
Two traders, Sam and Isabel, share a joint account. They have each been
|
||
studying Johnson & Johnson (JNJ), which is trading at around $63.35 per
|
||
share. Sam and Isabel, however, cannot agree on direction. Sam thinks
|
||
Johnson & Johnson will rise over the next five weeks, and Isabel believes it
|
||
will decline during that period.
|
||
Sam decides to buy the January 62.50 −65 call spread (January has 38
|
||
days until expiration in this example). Sam can buy this spread for 1.28. His
|
||
maximum risk is 1.28. This loss occurs if Johnson & Johnson is below
|
||
$62.50 at expiration, leaving both calls OTM. His maximum gain is 1.22,
|
||
realized if Johnson & Johnson is above $65 (65–62.50–1.28). With Johnson
|
||
& Johnson at $63.35, Sam’s delta is long 0.29 and his other greeks are
|
||
about flat.
|
||
Isabel decides to buy the January 62.50–65 put spread for a debit of 1.22.
|
||
Isabel’s biggest potential loss is 1.22, incurred if Johnson & Johnson is
|
||
above $65 a share at expiration, leaving both puts OTM. Her maximum
|
||
possible profit is 1.28, realized if the stock is below $62.50 at option
|
||
expiration. With Johnson & Johnson at $63.35, Isabel has a delta that is
|
||
short around 0.27 and is nearly flat gamma, theta, and vega.
|
||
Collectively, if both Sam and Isabel hold their trades until expiration, it’s
|
||
a zero-sum game. With Johnson & Johnson below $62.50, Sam loses his
|
||
investment of 1.28, but Isabel profits. She cancels out Sam’s loss by making
|
||
1.28. Above $65, Sam makes 1.22 while Isabel loses the same amount,
|
||
canceling out Sam’s gains. Between the two strikes, Sam has gains on his
|
||
62.50 call and Isabel has gains on her 65 put. The gains on the two options
|
||
will total 2.50, the combined total spent on the spreads—another draw.
|
||
EXHIBIT 9.12 Sam’s long call spread in Johnson & Johnson.
|
||
62.50–65 Call Spread
|
||
Delta +0.290
|
||
Gamma+0.001
|
||
Theta −0.004
|
||
Vega +0.006
|
||
EXHIBIT 9.13 Isabel’s long put spread in Johnson & Johnson.
|
||
62.50–65 Put Spread
|
||
Delta −0.273
|
||
Gamma−0.001
|
||
Theta +0.005
|
||
Vega −0.006
|
||
These two spreads were bought for a combined total of 2.50. The
|
||
collective position, composed of the four legs of these two spreads, forms a
|
||
new strategy altogether.
|
||
The two traders together have created a box. This box, which is empty of
|
||
both profit and loss, is represented by greeks that almost entirely offset each
|
||
other. Sam’s positive delta of 0.29 is mostly offset by Isabel’s −0.273 delta.
|
||
Gamma, theta, and vega will mostly offset each other, too.
|
||
Chapter 6 described a box as long synthetic stock combined with short
|
||
synthetic stock having a different strike price but the same expiration
|
||
month. It can also be defined, however, as two vertical spreads: a bull (bear)
|
||
call spread plus a bear (bull) put spread with the same strike prices and
|
||
expiration month.
|
||
The value of a box equals the present value of the distance between the
|
||
two strike prices (American-option models will also account for early
|
||
exercise potential in the box’s value). This 2.50 box, with 38 days until
|
||
expiration at a 1 percent interest rate, has less than a penny of interest
|
||
affecting its value. Boxes with more time until expiration will have a higher
|
||
interest rate component. If there was one year until expiration, the
|
||
combined value of the two verticals would equal 2.475. This is simply the
|
||
distance between the strikes minus interest (2.50–[2.50 × 0.01]).
|
||
Credit spreads are often made up of OTM options. Traders betting against
|
||
a stock rising through a certain price tend to sell OTM call spreads. For a
|
||
stock at $50 per share, they might sell the 55 calls and buy the 60 calls. But
|
||
because of the synthetic relationship that verticals have with one another,
|
||
the traders could buy an ITM put spread for the same exposure, after
|
||
accounting for interest. The traders could buy the 60 puts and sell the 55
|
||
puts. An ITM call (put) spread is synthetically equal to an OTM put (call)
|
||
spread.
|
||
Verticals and Beyond
|
||
Traders who want to take full advantage of all that options have to offer can
|
||
do so strategically by trading spreads. Vertical spreads truncate directional
|
||
risk compared with strategies like the covered call or single-legged option
|
||
trades. They also reduce option-specific risk, as indicated by their lower
|
||
gamma, theta, and vega. But lowering risk both in absolute terms and in the
|
||
greeks has a trade-off compared with buying options: limited profit
|
||
potential. This trade-off can be beneficial, depending on the trader’s
|
||
forecast. Debit spreads and credit spreads can be traded interchangeably to
|
||
achieve the same goals. When a long (short) call spread is combined with a
|
||
long (short) put spread, the product is a box. Chapter 10 describes other
|
||
ways vertical spreads can be combined to form positions that achieve
|
||
different trading objectives.
|
||
Note
|
||
1 . Note that it is customary when discussing the purchase or sale of
|
||
spreads to state the lower strike first, regardless of which is being bought
|
||
or sold. In this case, the trader is buying the 75–80 put spread.
|
||
CHAPTER 10
|
||
Wing Spreads
|
||
Condors and Butterflies
|
||
The “wing spread” family is a set of option strategies that is very popular,
|
||
particularly among experienced traders. These strategies make it possible
|
||
for speculators to accomplish something they could not possibly do by just
|
||
trading stocks: They provide a means to profit from a truly neutral market
|
||
in a security. Stocks that don’t move one iota can earn profits month after
|
||
month for income-generating traders who trade these strategies.
|
||
These types of spreads have a lot of moving parts and can be intimidating
|
||
to newcomers. At their heart, though, they are rather straightforward break-
|
||
even analysis trades that require little complex math to maintain. A simple
|
||
at-expiration diagram reveals in black and white the range in which the
|
||
underlying stock must remain in order to have a profitable position.
|
||
However, applying the greeks and some of the mathematics discussed in
|
||
previous chapters can help a trader understand these strategies on a deeper
|
||
level and maximize the chance of success. This chapter will discuss condors
|
||
and butterflies and how to put them into action most effectively.
|
||
Taking Flight
|
||
There are four primary wing spreads: the condor, the iron condor, the
|
||
butterfly, and the iron butterfly. Each of these spreads involves trading
|
||
multiple options with three or four strikes prices. We can take these spreads
|
||
at face value, we can consider each option as an individual component of
|
||
the spread, or we can view the spreads as being made up of two vertical
|
||
spreads.
|
||
Condor
|
||
A condor is a four-legged option strategy that enables a trader to capitalize
|
||
on volatility—increased or decreased. Traders can trade long or short iron
|
||
condors.
|
||
Long Condor
|
||
Long one call (put) with strike A; short one call (put) with a higher strike,
|
||
B; short one call (put) at strike C, which is higher than B; and long one call
|
||
(put) at strike D, which is higher than C. The distance between strike price
|
||
A and B is equal to the distance between strike C and strike D. The options
|
||
are all on the same security, in the same expiration cycle, and either all calls
|
||
or all puts.
|
||
Long Condor Example
|
||
Buy 1 XYZ November 70 call (A)
|
||
Sell 1 XYZ November 75 call (B)
|
||
Sell 1 XYZ November 90 call (C)
|
||
Buy 1 XYZ November 95 call (D)
|
||
Short Condor
|
||
Short one call (put) with strike A; long one call (put) with a higher strike, B;
|
||
long one call (put) with a strike, C, that is higher than B; and short one call
|
||
(put) with a strike, D, that is higher than C. The options must be on the
|
||
same security, in the same expiration cycle, and either all calls or all puts.
|
||
The differences in strike price between the vertical spread of strike prices A
|
||
and B and the strike prices of the vertical spread of strikes C and D are
|
||
equal.
|
||
Short Condor Example
|
||
Sell 1 XYZ November 70 call (A)
|
||
Buy 1 XYZ November 75 call (B)
|
||
Buy 1 XYZ November 90 call (C)
|
||
Sell 1 XYZ November 95 call (D)
|
||
Iron Condor
|
||
An iron condor is similar to a condor, but with a mix of both calls and puts.
|
||
Essentially, the condor and iron condor are synthetically the same.
|
||
Short Iron Condor
|
||
Long one put with strike A; short one put with a higher strike, B; short one
|
||
call with an even higher strike, C; and long one call with a still higher
|
||
strike, D. The options are on the same security and in the same expiration
|
||
cycle. The put credit spread has the same distance between the strike prices
|
||
as the call credit spread.
|
||
Short Iron Condor Example
|
||
Buy 1 XYZ November 70 put (A)
|
||
Sell 1 XYZ November 75 put (B)
|
||
Sell 1 XYZ November 90 call (C)
|
||
Buy 1 XYZ November 95 call (D)
|
||
Long Iron Condor
|
||
Short one put with strike A; long one put with a higher strike, B; long one
|
||
call with an even higher strike, C; and short one call with a still higher
|
||
strike, D. The options are on the same security and in the same expiration
|
||
cycle. The put debit spread (strikes A and B) has the same distance between
|
||
the strike prices as the call debit spread (strikes C and D).
|
||
Long Iron Condor Example
|
||
Sell 1 XYZ November 70 put (A)
|
||
Buy 1 XYZ November 75 put (B)
|
||
Buy 1 XYZ November 90 call (C)
|
||
Sell 1 XYZ November 95 call (D)
|
||
Butterflies
|
||
Butterflies are wing spreads similar to condors, but there are only three
|
||
strikes involved in the trade—not four.
|
||
Long Butterfly
|
||
Long one call (put) with strike A; short two calls (puts) with a higher strike,
|
||
B; and long one call (put) with an even higher strike, C. The options are on
|
||
the same security, in the same expiration cycle, and are either all calls or all
|
||
puts. The difference in price between strikes A and B equals that between
|
||
strikes B and C.
|
||
Long Butterfly Example
|
||
Buy 1 XYZ December 50 call (A)
|
||
Sell 2 XYZ December 60 call (B)
|
||
Buy 1 XYZ December 70 call (C)
|
||
Short Butterfly
|
||
Short one call (put) with strike A; long two calls (puts) with a higher strike,
|
||
B; and short one call (put) with an even higher strike, C. The options are on
|
||
the same security, in the same expiration cycle, and are either all calls or all
|
||
puts. The vertical spread made up of the options with strike A and strike B
|
||
has the same distance between the strike prices of the vertical spread made
|
||
up of the options with strike B and strike C.
|
||
Short Butterfly Example
|
||
Sell 1 XYZ December 50 call
|
||
Buy 2 XYZ December 60 call
|
||
Sell 1 XYZ December 70 call
|
||
Iron Butterflies
|
||
Much like the relationship of the condor to the iron condor, a butterfly has
|
||
its synthetic equal as well: the iron butterfly.
|
||
Short Iron Butterfly
|
||
Long one put with strike A; short one put with a higher strike, B; short one
|
||
call with strike B; long one call with a strike higher than B, C. The options
|
||
are on the same security and in the same expiration cycle. The distances
|
||
between the strikes of the put spread and between the strikes of the call
|
||
spread are equal.
|
||
Short Iron Butterfly Example
|
||
Buy 1 XYZ December 50 put (A)
|
||
Sell 1 XYZ December 60 put (B)
|
||
Sell 1 XYZ December 60 call (B)
|
||
Buy 1 XYZ December 70 call (C)
|
||
Long Iron Butterfly
|
||
Short one put with strike A; long one put with a higher strike, B; long one
|
||
call with strike B; short one call with a strike higher than B, C. The options
|
||
are on the same security and in the same expiration cycle. The distances
|
||
between the strikes of the put spread and between the strikes of the call
|
||
spread are equal. The put debit spread has the same distance between the
|
||
strike prices as the call debit spread.
|
||
Long Iron Butterfly Example
|
||
Sell 1 XYZ December 50 put
|
||
Buy 1 XYZ December 60 put
|
||
Buy 1 XYZ December 60 call
|
||
Sell 1 XYZ December 70 call
|
||
These spreads were defined in terms of both long and short for each
|
||
strategy. Whether the spread is classified as long or short depends on
|
||
whether it was established at a credit or a debit. Debit condors or butterflies
|
||
are considered long spreads. And credit condors or butterflies are
|
||
considered short spreads.
|
||
The words long and short mean little, though in terms of the spread as a
|
||
whole. The important thing is which strikes have long options and which
|
||
have short options. A call debit spread is synthetically equal to a put credit
|
||
spread on the same security, with the same expiration month and strike
|
||
prices. That means a long condor is synthetically equal to a short iron
|
||
condor, and a long butterfly is synthetically equal to a short iron butterfly,
|
||
when the same strikes are used. Whichever position is constructed, the best-
|
||
case scenario is to have debit spreads expire with both options in-the-money
|
||
(ITM) and credit spreads expire with both options out-of-the-money
|
||
(OTM).
|
||
Many retail traders prefer trading these spreads for the purpose of
|
||
generating income. In this case, a trader would sell the guts, or middle
|
||
strikes, and buy the wings, or outer strikes. When a trader is short the guts,
|
||
low realized volatility is usually the objective. For long butterflies and short
|
||
iron butterflies, the stock needs to be right at the middle strike for the
|
||
maximum payout. For long condors and short iron condors, the stock needs
|
||
to be between the short strikes at expiration for maximum payout. In both
|
||
instances, the wings are bought to limit potential losses of the otherwise
|
||
naked options.
|
||
Long Butterfly Example
|
||
A trader, Kathleen, has been studying United Parcel Service (UPS), which
|
||
is trading at around $70.65. She believes UPS will trade sideways until July
|
||
expiration. Kathleen buys the July 65–70–75 butterfly for 2.00. She
|
||
executes the following legs:
|
||
Kathleen looks at her trade as two vertical spreads, the 65–70 bull (debit)
|
||
call spread and the 70–75 bear (credit) call spread. Intuitively, she would
|
||
want UPS to be at or above $70 at expiration for her bull call spread to have
|
||
maximum value. But she has the seemingly conflicting goal of also wanting
|
||
UPS to be at or below $70 to get the most from her 70–75 bear call spread.
|
||
The ideal price for the stock to be trading at expiration in this example is
|
||
right at $70 per share—the best of both worlds. The at-expiration diagram,
|
||
Exhibit 10.1 , shows the profit or loss of all possible outcomes at expiration.
|
||
EXHIBIT 10.1 UPS 65–70–75 butterfly.
|
||
If the price of UPS shares declines below $65 at expiration, all these calls
|
||
will expire. The entire 2.00 spent on the trade will be lost. If UPS is above
|
||
$65 at expiration, the 65 call will be ITM and will be exercised. The call
|
||
will profit like a long position in 100 shares of the underlying. The
|
||
maximum profit is reached if UPS is at $70 at expiration. Kathleen makes a
|
||
5.00 profit from $65 to $70 on her 65 calls. But because she paid 2.00
|
||
initially for the spread, her net profit at $70 is just 3.00. If UPS is above $70
|
||
a share at expiration in this example, the two 70 calls will be assigned. The
|
||
assignment of one call will offset the long stock acquired by the 65 calls
|
||
being exercised. Assignment of the other call will create a short position in
|
||
the underlying. That short position loses as UPS moves higher up to $75 a
|
||
share, eating away at the 3.00 profit. If UPS is above $75 at expiration, the
|
||
75 call can be exercised to buy back the short stock position that resulted
|
||
from the 70’s being assigned. The loss on the short stock between $70 and
|
||
$75 will cost Kathleen 5.00, stripping her of her 3.00 profit and giving her a
|
||
net loss of 2.00 to boot. End result? Above $75 at expiration, she has no
|
||
position in the underlying and loses 2.00.
|
||
A butterfly is a break-even analysis trade . This name refers to the idea
|
||
that the most important considerations in this strategy are the breakeven
|
||
points. The at-expiration diagram, Exhibit 10.2 , shows the break-even
|
||
prices for this trade.
|
||
EXHIBIT 10.2 UPS 65–70–75 butterfly breakevens.
|
||
If the position is held until expiration and UPS is between $65 and $70 at
|
||
that time, the 65 calls are exercised, resulting in long stock. The effective
|
||
purchase price of that stock is $67. That’s the strike price plus the cost of
|
||
the spread; that’s the lower break-even price. The other break-even is at
|
||
$73. The net short position of 100 shares resulting from assignment of the
|
||
70 call loses more as the stock rises between $70 and $75. The entire 3.00
|
||
profit realized at the $70 share price is eroded when the stock reaches $73.
|
||
Above $73, the trade produces a loss.
|
||
Kathleen’s trading objective is to profit from UPS trading between $67
|
||
and $73 at expiration. The best-case scenario is that it declines only slightly
|
||
from its price of $70.65 when the trade is established, to $70 per share.
|
||
Alternatives
|
||
Kathleen had other alternative positions she could have traded to meet her
|
||
goals. An iron butterfly with the same strike prices would have shown about
|
||
the same risk/reward picture, because the two positions are synthetically
|
||
equivalent. But there may, in some cases, be a slight advantage to trading
|
||
the iron butterfly over the long butterfly. The iron butterfly uses OTM put
|
||
options instead of ITM calls, meaning the bid-ask spreads may be tighter.
|
||
This means giving up less edge to the liquidity providers.
|
||
She could have also bought a condor or sold an iron condor. With condor-
|
||
family spreads, there is a lower maximum profit potential but a wider range
|
||
in which that maximum payout takes place. For example, Kathleen could
|
||
have executed the following legs to establish an iron condor:
|
||
Essentially, Kathleen would be selling two credit spreads: the July 60–65
|
||
put spread for 0.30 and the July 75–80 call spread for 0.35. Exhibit 10.3
|
||
shows the payout at expiration of the UPS July 60–65–75–80 iron condor.
|
||
EXHIBIT 10.3 UPS 60–65–75–80 iron condor.
|
||
Although the forecast and trading objectives may be similar to those for
|
||
the butterfly, the payout diagram reveals some important differences. First,
|
||
the maximum loss is significantly higher with a condor or iron condor. In
|
||
this case, the maximum loss is 4.35. This unfortunate situation would occur
|
||
if UPS were to drop to below $60 or rise above $80 by expiration. Below
|
||
$60, the call spread expires, netting 0.35. But the put spread is ITM.
|
||
Kathleen would lose a net of 4.70 on the put spread. The gain on the call
|
||
spread combined with the loss on the put spread makes the trade a loser of
|
||
4.35 if the stock is below $60 at expiration. Above $80, the put spread is
|
||
worthless, earning 0.30, but the call spread is a loser by 4.65. The gain on
|
||
the put spread plus the loss on the call spread is a net loser of 4.35. Between
|
||
$65 and $75, all options expire and the 0.65 credit is all profit.
|
||
So far, this looks like a pretty lousy alternative to the butterfly. You can
|
||
lose 4.35 but only make 0.65! Could there be any good reason for making
|
||
this trade? Maybe. The difference is wiggle room. The breakevens are 2.65
|
||
wider in each direction with the iron condor. Exhibit 10.4 shows these
|
||
prices on the graph.
|
||
EXHIBIT 10.4 UPS 60–65–75–80 iron condor breakevens.
|
||
The lower threshold for profit occurs at $64.35 and the upper at $75.65.
|
||
With condor/iron condors, there can be a greater chance of producing a
|
||
winning trade because the range is wider than that of the butterfly. This
|
||
benefit, however, has a trade-off of lower potential profit. There is always a
|
||
parallel relationship of risk and reward. When risk increases so does
|
||
reward, and vice versa. This way of thinking should now be ingrained in
|
||
your DNA. The risk of failure is less, so the payout is less. Because the
|
||
odds of winning are higher, a trader will accept lower payouts on the trade.
|
||
Keys to Success
|
||
No matter which trade is more suitable to Kathleen’s risk tolerance, the
|
||
overall concept is the same: profit from little directional movement. Before
|
||
Kathleen found a stock on which to trade her spread, she will have sifted
|
||
through myriad stocks to find those that she expects to trade in a range. She
|
||
has a few tools in her trading toolbox to help her find good butterfly and
|
||
condor candidates.
|
||
First, Kathleen can use technical analysis as a guide. This is a rather
|
||
straightforward litmus test: does the stock chart show a trending, volatile
|
||
stock or a flat, nonvolatile stock? For the condor, a quick glance at the past
|
||
few months will reveal whether the stock traded between $65 and $75. If it
|
||
did, it might be a good iron condor candidate. Although this very simplistic
|
||
approach is often enough for many traders, those who like lots of graphs
|
||
and numbers can use their favorite analyses to confirm that the stock is
|
||
trading in a range. Drawing trendlines can help traders to visualize the
|
||
channel in which a stock has been trading. Knowing support and resistance
|
||
is also beneficial. The average directional movement index (ADX) or
|
||
moving average converging/diverging (MACD) indicator can help to show
|
||
if there is a trend present. If there is, the stock may not be a good candidate.
|
||
Second, Kathleen can use fundamentals. Kathleen wants stocks with
|
||
nothing on their agendas. She wants to avoid stocks that have pending
|
||
events that could cause their share price to move too much. Events to avoid
|
||
are earnings releases and other major announcements that could have an
|
||
impact on the stock price. For example, a drug stock that has been trading
|
||
in a range because it is awaiting Food and Drug Administration (FDA)
|
||
approval, which is expected to occur over the next month, is not a good
|
||
candidate for this sort of trade.
|
||
The last thing to consider is whether the numbers make sense. Kathleen’s
|
||
iron condor risks 4.35 to make 0.65. Whether this sounds like a good trade
|
||
depends on Kathleen’s risk tolerance and the general environment of UPS,
|
||
the industry, and the market as a whole. In some environments, the
|
||
0.65/4.35 payout-to-risk ratio makes a lot of sense. For other people, other
|
||
stocks, and other environments, it doesn’t.
|
||
Greeks and Wing Spreads
|
||
Much of this chapter has been spent on how wing spreads perform if held
|
||
until expiration, and little has been said of option greeks and their role in
|
||
wing spreads. Greeks do come into play with butterflies and condors but not
|
||
necessarily the same way they do with other types of option trades.
|
||
The vegas on these types of spreads are smaller than they are on many
|
||
other types of strategies. For a typical nonprofessional trader, it’s hard to
|
||
trade implied volatility with condors or butterflies. The collective
|
||
commissions on the four legs, as well as margin and capital considerations,
|
||
put these out of reach for active trading. Professional traders and retail
|
||
traders subject to portfolio margining are better equipped for volatility
|
||
trading with these spreads.
|
||
The true strength of wing spreads, however, is in looking at them as
|
||
break-even analysis trades much like vertical spreads. The trade is a winner
|
||
if it is on the correct side of the break-even price. Wing spreads, however,
|
||
are a combination of two vertical spreads, so there are two break-even
|
||
prices. One of the verticals is guaranteed to be a winner. The stock can be
|
||
either higher or lower at expiration—not both. In some cases, both verticals
|
||
can be winners.
|
||
Consider an iron condor. Instead of reaping one premium from selling one
|
||
OTM call credit spread, iron condor sellers double dip by additionally
|
||
selling an OTM put credit spread. They collect a double credit, but only one
|
||
of the credit spreads can be a loser at expiration. The trader, however, does
|
||
have to worry about both directions independently.
|
||
There are two ways for greeks and volatility analysis to help traders trade
|
||
wing spreads. One of them involves using delta and theta as tools to trade a
|
||
directional spread. The other uses implied volatility in strike selection
|
||
decisions.
|
||
Directional Butterflies
|
||
Trading a butterfly can be an excellent way to establish a low-cost,
|
||
relatively low-risk directional trade when a trader has a specific price target
|
||
in mind. For example, a trader, Ross, has been studying Walgreen Co.
|
||
(WAG) and believes it will rise from its current level of $33.50 to $36 per
|
||
share over the next month. Ross buys a butterfly consisting of all OTM
|
||
January calls with 31 days until expiration.
|
||
He executes the following legs:
|
||
As a directional trade alternative, Ross could have bought just the January
|
||
35 call for 1.15. As a cheaper alternative, he could have also bought the 35–
|
||
36 bull call spread for 0.35. In fact, Ross actually does buy the 35–36
|
||
spread, but he also sells the January 36–37 call spread at 0.25 to reduce the
|
||
cost of the bull call spread, investing only a dime. The benefit of lower cost,
|
||
however, comes with trade-offs. Exhibit 10.5 compares the bull call spread
|
||
with a bullish butterfly.
|
||
EXHIBIT 10.5 Bull call spread vs. bull butterfly (Walgreen Co. at $33.50).
|
||
|
||
The butterfly has lower nominal risk—only 0.10 compared with 0.35 for
|
||
the call spread. The maximum reward is higher in nominal terms, too—0.90
|
||
versus 0.65. The trade-off is what is given up. With both strategies, the goal
|
||
is to have Walgreen Co. at $36 around expiration. But the bull call spread
|
||
has more room for error to the upside. If the stock trades a lot higher than
|
||
expected, the butterfly can end up being a losing trade.
|
||
Given Ross’s expectations in this example, this might be a risk he is
|
||
willing to take. He doesn’t expect Walgreen Co. to close right at $36 on the
|
||
expiration date. It could happen, but it’s unlikely. However, he’d have to be
|
||
wildly wrong to have the trade be a loser on the upside. It would be a much
|
||
larger move than expected for the stock to rise significantly above $36. If
|
||
Ross strongly believes Walgreen Co. can be around $36 at expiration, the
|
||
cost benefit of 0.10 vs. 0.35 may offset the upside risk above $37. As a
|
||
general rule, directional butterflies work well in trending, low-volatility
|
||
stocks.
|
||
When Ross monitors his butterfly, he will want to see the greeks for this
|
||
position as well. Exhibit 10.6 shows the trade’s analytics with Walgreen Co.
|
||
at $33.50.
|
||
EXHIBIT 10.6 Walgreen Co. 35–36–37 butterfly greeks (stock at $33.50,
|
||
31 days to expiration).
|
||
Delta +0.008
|
||
Gamma−0.004
|
||
Theta +0.001
|
||
Vega −0.001
|
||
When the trade is first put on, the delta is small—only +0.008. Gamma is
|
||
slightly negative and theta is very slightly positive. This is important
|
||
information if Walgreen Co.’s ascent happens sooner than Ross planned.
|
||
The trade will show just a small profit if the stock jumps to $36 per share
|
||
right away. Ross’s theoretical gain will be almost unnoticeable. At $36 per
|
||
share, the position will have its highest theta, which will increase as
|
||
expiration approaches. Ross will have to wait for time to pass to see the
|
||
trade reach its full potential.
|
||
This example shows the interrelation between delta and theta. We know
|
||
from an at-expiration analysis that if Walgreen Co. moves from $33.50 to
|
||
$36, the butterfly’s profit will be 0.90 (the spread of $1 minus the 0.10
|
||
initial debit). If we distribute the 0.90 profit over the 2.50 move from
|
||
$33.50 to $36, the butterfly gains about 0.36 per dollar move in Walgreen
|
||
Co. (0.90/(36 − 33.50). This implies a delta of about 0.36.
|
||
But the delta, with 31 days until expiration and Walgreen Co. at $33.50, is
|
||
only 0.008, and because of negative gamma this delta will get even smaller
|
||
as Walgreen Co. rises. Butterflies, like the vertical spreads of which they are
|
||
composed, can profit from direction but are never purely directional trades.
|
||
Time is always a factor. It is theta, working in tandem with delta, that
|
||
contributes to profit or peril.
|
||
A bearish butterfly can be constructed as well. One would execute the
|
||
trade with all OTM puts or all ITM calls. The concept is the same: sell the
|
||
guts at the strike at which the stock is expected to be trading at expiration,
|
||
and buy the wings for protection.
|
||
Constructing Trades to Maximize
|
||
Profit
|
||
Many traders who focus on trading iron condors trade exchange-traded
|
||
funds (ETFs) or indexes. Why? Diversification. Because indexes are made
|
||
up of many stocks, they usually don’t have big gaps caused by surprise
|
||
earnings announcements, takeovers, or other company-specific events. But
|
||
it’s not just selecting the right underlying to trade that is the challenge. A
|
||
trader also needs to pick the right strike prices. Finding the right strike
|
||
prices to trade can be something of an art, although science can help, as
|
||
well.
|
||
Three Looks at the Condor
|
||
Strike selection is essential for a successful condor. If strikes are too close
|
||
together or two far apart, the trade can become much less attractive.
|
||
Strikes Too Close
|
||
The QQQs are options on the ETFs that track the Nasdaq 100 (QQQ). They
|
||
have strikes in $1 increments, giving traders a lot to choose from. With
|
||
QQQ trading at around $55.95, consider the 54–55–57–58 iron condor. In
|
||
this example, with 31 days until expiration, the following legs can be
|
||
executed:
|
||
In this trade, the maximum profit is 0.63. The maximum risk is 0.37. This
|
||
isn’t a bad profit-to-loss ratio. The break-even price on the downside is
|
||
$54.37 and on the upside is $57.63. That’s a $3.26 range—a tight space for
|
||
a mover like the QQQ to occupy in a month. The ETF can drop about only
|
||
2.8 percent or rise 3 percent before the trade becomes a loser. No one needs
|
||
any fancy math to show that this is likely a losing proposition in the long
|
||
run. While choosing closer strikes can lead to higher premiums, the range
|
||
can be so constricting that it asphyxiates the possibility of profit.
|
||
Strikes Too Far
|
||
Strikes too far apart can make for impractical trades as well. Exhibit 10.7
|
||
shows an options chain for the Dow Jones Industrial Average Index (DJX).
|
||
These prices are from around 2007 when implied volatility (IV) was
|
||
historically low, making the OTM options fairly low priced. In this
|
||
example, DJX is around $135.20 and there are 51 days until expiration.
|
||
EXHIBIT 10.7 Options chain for DJIA.
|
||
If the goal is to choose strikes that are far enough apart to be unlikely to
|
||
come into play, a trader might be tempted to trade the 120–123–142–145
|
||
iron condor. With this wingspan, there is certainly a good chance of staying
|
||
between those strikes—you could drive a proverbial truck through that
|
||
range.
|
||
This would be a great trade if it weren’t for the prices one would have to
|
||
accept to put it on. First, the 120 puts are offered at 0.25 and the 123 puts
|
||
are 0.25 bid. This means that the put spread would be sold at zero! The
|
||
maximum risk is 3.00, and the maximum gain is zero. Not a really good
|
||
risk/reward. The 142–145 call spread isn’t much better: it can be sold for a
|
||
dime.
|
||
At the time, again a low-volatility period, many traders probably felt it
|
||
was unlikely that the DJX will rise 5 percent in a 51-day period. Some
|
||
traders may have considered trading a similarly priced iron condor (though
|
||
of course they’d have to require some small credit for the risk). A little over
|
||
a year later the DJX was trading around 50 percent lower. Traders must
|
||
always be vigilant of the possibility of volatility, even unexpected volatility
|
||
and structure their risk/reward accordingly. Most traders would say the
|
||
risk/reward of this trade isn’t worth it. Strikes too far apart have a greater
|
||
chance of success, but the payoff just isn’t there.
|
||
Strikes with High Probabilities of Success
|
||
So how does a trader find the happy medium of strikes close enough
|
||
together to provide rich premiums but far enough apart to have a good
|
||
chance of success? Certainly, there is something to be said for looking at
|
||
the prices at which a trade can be done and having a subjective feel for
|
||
whether the underlying is likely to move outside the range of the break-
|
||
even prices. A little math, however, can help quantify this likelihood and aid
|
||
in the decision-making process.
|
||
Recall that IV is read by many traders to be the market’s consensus
|
||
estimate of future realized volatility in terms of annualized standard
|
||
deviation. While that is a mouthful to say—or in this case, rather, an eyeful
|
||
to read—when broken down it is not quite as intimidating as it sounds.
|
||
Consider a simplified example in which an underlying security is trading at
|
||
$100 a share and the implied volatility of the at-the-money (ATM) options
|
||
is 10 percent. That means, from a statistical perspective, that if the expected
|
||
return for the stock is unchanged, the one-year standard deviations are at
|
||
$90 and $110. 1 In this case, there is about a 68 percent chance of the stock
|
||
trading between $90 and $110 one year from now. IV then is useful
|
||
information to a trader who wants to quantify the chances of an iron
|
||
condor’s expiring profitable, but there are a few adjustments that need to be
|
||
made.
|
||
First, because with an iron condor the idea is to profit from net short
|
||
option premium, it usually makes more sense to sell shorter-term options to
|
||
profit from higher rates of time decay. This entails trading condors
|
||
composed of one- or two-month options. The IV needs to be deannualized
|
||
and converted to represent the standard deviation of the underlying at
|
||
expiration.
|
||
The first step is to compute the one-day standard deviation. This is found
|
||
by dividing the implied volatility by the square root of the number of
|
||
trading days in a year, then multiplying by the square root of the number of
|
||
trading days until expiration. The result is the standard deviation (σ) at the
|
||
time of expiration stated as a percent. Next, multiply that percentage by the
|
||
price of the underlying to get the standard deviation in absolute terms.
|
||
The formula 2 for calculating the shorter-term standard deviation is as
|
||
follows:
|
||
This value will be added to or subtracted from the price of the underlying
|
||
to get the price points at which the approximate standard deviations fall.
|
||
Consider an example using options on the Standard & Poor’s 500 Index
|
||
(SPX). With 50 days until expiration, the SPX is at 1241 and the implied
|
||
volatility is 23.2 percent. To find strike prices that are one standard
|
||
deviation away from the current index price, we need to enter the values
|
||
into the equation. We first need to know how many actual trading days are
|
||
in the 50-day period. There are 35 business days during this particular 50-
|
||
day period (there is one holiday and seven weekend days). We now have all
|
||
the data we need to calculate which strikes to sell.
|
||
The lower standard deviation is 1134.55 (1241 − 106.45) and the upper is
|
||
1347.45 (1241 + 106.45). This means there would be about a 68 percent
|
||
chance of SPX ending up between 1134.55 and 1347.45 at expiration. In
|
||
this example, to have about a two-thirds chance of success, one would sell
|
||
the 1135 puts and the 1350 calls as part of the iron condor.
|
||
Being Selective
|
||
There is about a two-thirds chance of the underlying staying between the
|
||
upper and lower standard deviation points and about a one-third chance it
|
||
won’t. Reasonably good odds. But the maximum loss of an iron condor will
|
||
be more than the maximum profit potential. In fact, the max-profit-to-max-
|
||
loss ratio is usually less than 1 to 3. For every $1 that can be made, often $4
|
||
or $5 will be at risk.
|
||
The pricing model determines fair value of an option based on the implied
|
||
volatility set by the market. Again, many traders consider IV to be the
|
||
market’s consensus estimate of future realized volatility. Assuming the
|
||
market is generally right and options are efficiently priced, in the long run,
|
||
future stock volatility should be about the same as the implied volatility
|
||
from options prices. That means that if all of your options trades are
|
||
executed at fair value, you are likely to break even in the long run. The
|
||
caveat is that whether the options market is efficient or not, retail or
|
||
institutional traders cannot generally execute trades at fair value. They have
|
||
to sell the bid (sell below theoretical value) and buy the offer (buy above
|
||
theoretical value). This gives the trade a statistical disadvantage, called
|
||
giving up the edge, from an expected return perspective.
|
||
Even though you are more likely to win than to lose with each individual
|
||
trade when strikes are sold at the one-standard-deviation point, the edge
|
||
given up to the market in conjunction with the higher price tag on losers
|
||
makes the trade a statistical loser in the long run. While this means for
|
||
certain that the non-market-making trader is at a constant disadvantage,
|
||
trading condors and butterflies is no different from any other strategy.
|
||
Giving up the edge is the plight of retail and institutional traders. To profit
|
||
in the long run, a trader needs to beat the market, which requires careful
|
||
planning, selectivity, and risk management.
|
||
Savvy traders trade iron condors with strikes one standard deviation away
|
||
from the current stock price only when they think there is more than a two-
|
||
thirds chance of market neutrality. In other words, if you think the market
|
||
will be less volatile than the prices in the options market imply, sell the iron
|
||
condor or trade another such premium-selling strategy. As discussed above,
|
||
this opinion should reflect sound judgment based on some combination of
|
||
technical analysis, fundamental analysis, volatility analysis, feel, and
|
||
subjectivity.
|
||
A Safe Landing for an Iron Condor
|
||
Although traders can’t control what the market does, they can control how
|
||
they react to the market. Assume a trader has done due diligence in studying
|
||
a stock and feels it is a qualified candidate for a neutral strategy. With the
|
||
stock at $90, a 16.5 percent implied volatility, and 41 days until expiration,
|
||
the standard deviation is about 5. The trader sells the following iron condor:
|
||
With the stock at $90, directly between the two short strikes, the trade is
|
||
direction neutral. The maximum profit is equal to the total premium taken
|
||
in, which in this case is $800. The maximum loss is $4,200. There is about
|
||
a two-thirds chance of retaining the $800 at expiration.
|
||
After one week, the overall market begins trending higher on unexpected
|
||
bullish economic news. This stock follows suit and is now trading at $93,
|
||
and concern is mounting that the rally will continue. The value of the spread
|
||
now is about 1.10 per contract (we ignore slippage from trading on the bid-
|
||
ask spreads of the four legs of the spread). This means the trade has lost
|
||
$300 because it would cost $1,100 to buy back what the trader sold for a
|
||
total of $800.
|
||
One strategy for managing this trade looking forward is inaction. The
|
||
philosophy is that sometimes these trades just don’t work out and you take
|
||
your lumps. The philosophy is that the winners should outweigh the losers
|
||
over the long term. For some of the more talented and successful traders
|
||
with a proven track record, this may be a viable strategy, but there are more
|
||
active options as well. A trader can either close the spread or adjust it.
|
||
The two sets of data that must be considered in this decision are the prices
|
||
of the individual options and the greeks for the trade. Exhibit 10.8 shows
|
||
the new data with the stock at $93.
|
||
EXHIBIT 10.8 Greeks for iron condor with stock at $93.
|
||
The trade is no longer neutral, as it was when the underlying was at $90.
|
||
It now has a delta of −2.54, which is like being short 254 shares of the
|
||
underlying. Although the more time that passes the better—as indicated by
|
||
the +0.230 theta—delta is of the utmost concern. The trader has now found
|
||
himself short a market that he thinks may rally.
|
||
Closing the entire position is one alternative. To be sure, if you don’t have
|
||
an opinion on the underlying, you shouldn’t have a position. It’s like
|
||
making a bet on a sporting event when you don’t really know who you
|
||
think will win. The spread can also be dismantled piecemeal. First, the 85
|
||
puts are valued at $0.07 each. Buying these back is a no-brainer. In the
|
||
event the stock does retrace, why have the positive delta of that leg working
|
||
against you when you can eliminate the risk inexpensively now?
|
||
The 80 puts are worthless, offered at 0.05, presumably. There is no point
|
||
in trying to sell these. If the market does turn around, they may benefit,
|
||
resulting in an unexpected profit.
|
||
The 80 and 85 puts are the least of his worries, though. The concern is a
|
||
continuing rally. Clearly, the greater risk is in the 95–100 call spread.
|
||
Closing the call spread for a loss eliminates the possibility of future losses
|
||
and may be a wise choice, especially if there is great uncertainty. Taking a
|
||
small loss now of only around $300 is a better trade than risking a total loss
|
||
of $4,200 when you think there is a strong chance of that total loss
|
||
occurring.
|
||
But if the trader is not merely concerned that the stock will rally but truly
|
||
believes that there is a good chance it will, the most logical action is to
|
||
position himself for that expected move. Although there are many ways to
|
||
accomplish this, the simplest way is to buy to close the 95 calls to eliminate
|
||
the position at that strike. This eliminates the short delta from the 95 calls,
|
||
leading to a now-positive delta for the position as a whole. The new
|
||
position after adjusting by buying the 85 puts and the 95 calls is shown in
|
||
Exhibit 10.9 .
|
||
EXHIBIT 10.9 Iron condor adjusted to strangle.
|
||
The result is a long strangle: a long call and a long put of the same month
|
||
with two different strikes. Strangles will be discussed in subsequent
|
||
chapters. The 80 puts are far enough out-of-the-money to be fairly
|
||
irrelevant. Effectively, the position is long ten 100-strike calls. This serves
|
||
the purpose of changing the negative 2.54 delta into a positive 0.96 delta.
|
||
The trader now has a bullish position in the stock that he thinks will rally—
|
||
a much smarter position, given that forecast.
|
||
The Retail Trader versus the Pro
|
||
Iron condors are very popular trades among retail traders. These days one
|
||
can hardly go to a cocktail party and mention the word options without
|
||
hearing someone tell a story about an iron condor on which he’s made a
|
||
bundle of money trading. Strangely, no one ever tells stories about trades in
|
||
which he has lost a bundle of money.
|
||
Two of the strengths of this strategy that attract retail traders are its
|
||
limited risk and high probability of success. Another draw of this type of
|
||
strategy is that the iron condor and the other wing spreads offer something
|
||
truly unique to the retail trader: a way to profit from stocks that don’t move.
|
||
In the stock-trading world, the only thing that can be traded is direction—
|
||
that is, delta. The iron condor is an approachable way for a nonprofessional
|
||
to dabble in nonlinear trading. The iron condor does a good job in
|
||
eliminating delta—unless, of course, the stock moves and gamma kicks in.
|
||
It is efficient in helping income-generating retail traders accomplish their
|
||
goals. And when a loss occurs, although it can be bigger than the potential
|
||
profits, it is finite.
|
||
But professional option traders, who have access to lots of capital and
|
||
have very low commissions and margin requirements, tend to focus their
|
||
efforts in other directions: they tend to trade volatility. Although iron
|
||
condors are well equipped for profiting from theta when the stock
|
||
cooperates, it is also possible to trade implied volatility with this strategy.
|
||
The examples of iron condors, condors, iron butterflies, and butterflies
|
||
presented in this chapter so far have for the most part been from the
|
||
perspective of the neutral trader: selling the guts and buying the wings. A
|
||
trader focusing on vega in any of these strategies may do just the opposite
|
||
—buy the guts and sell the wings—depending on whether the trader is
|
||
bullish or bearish on volatility.
|
||
Say a trader, Joe, had a bullish outlook on volatility in Salesforce.com
|
||
(CRM). Joe could sell the following condor 100 times.
|
||
In this example, February is 59 days from expiration. Exhibit 10.10 shows
|
||
the analytics for this trade with CRM at $104.32.
|
||
EXHIBIT 10.10 Salesforce.com condor ( Salesforce.com at $104.32).
|
||
As expected with the underlying centered between the two middle strikes,
|
||
delta and gamma are about flat. As Salesforce.com moves higher or lower,
|
||
though, gamma and, consequently, delta will change. As the stock moves
|
||
closer to either of the long strikes, gamma will become more positive,
|
||
causing the delta to change favorably for Joe. Theta, however, is working
|
||
against him with Salesforce.com at $104.32, costing $150 a day. In this
|
||
instance, movement is good. Joe benefits from increased realized volatility.
|
||
The best-case scenario would be if Salesforce.com moves through either of
|
||
the long strikes to, or through, either of the short strikes.
|
||
The prime objective in this example, though, is to profit from a rise in IV.
|
||
The position has a positive vega. The position makes or loses $400 with
|
||
every point change in implied volatility. Because of the proportion of theta
|
||
risk to vega risk, this should be a short-term play.
|
||
If Joe were looking for a small rise in IV, say five points, the move would
|
||
have to happen within 13 calendar days, given the vega and theta figures.
|
||
The vega gain on a rise of five vol points would be $2,000, and the theta
|
||
loss over 13 calendar days would be $1,950. If there were stock movement
|
||
associated with the IV increase, that delta/gamma gain would offset some of
|
||
the havoc that theta wreaked on the option premiums. However, if Joe
|
||
traded a strategy like a condor as a vol play, he would likely expect a bigger
|
||
volatility move than the five points discussed here as well as expecting
|
||
increased realized volatility.
|
||
A condor bullish vol play works when you expect something to change a
|
||
stock’s price action in the short term. Examples would be rumors of a new
|
||
product’s being unveiled, a product recall, a management change, or some
|
||
other shake-up that leads to greater uncertainty about the company’s future
|
||
—good or bad. The goal is to profit from a rise in IV, so the trade needs to
|
||
be put on before the announcement occurs. The motto in option-volatility
|
||
trading is “Buy the rumor; sell the news.” Usually, by the time the news is
|
||
out, the increase in IV is already priced into option premiums. As
|
||
uncertainty decreases, IV decreases as well.
|
||
Notes
|
||
1 . It is important to note that in the real world, interest and expectations
|
||
for future stock-price movement come into play. For simplicity’s sake,
|
||
they’ve been excluded here.
|
||
2 . This is an approximate formula for estimating standard deviation.
|
||
Although it is mathematically only an approximation, it is the convention
|
||
used by many option traders. It is a traders’ short cut.
|
||
CHAPTER 11
|
||
Calendar and Diagonal Spreads
|
||
Option selling is a niche that attracts many retail and professional traders
|
||
because it’s possible to profit from the passage of time. Calendar and
|
||
diagonal spreads are practical strategies to limit risk while profiting from
|
||
time. But these spreads are unique in many ways. In order to be successful
|
||
with them, it is important to understand their subtle qualities.
|
||
Calendar Spreads
|
||
Definition : A calendar spread, sometimes called a time spread or a
|
||
horizontal spread , is an option strategy that involves buying one option and
|
||
selling another option with the same strike price but with a different
|
||
expiration date.
|
||
At-expiration diagrams do a calendar-spread trader little good. Why? At
|
||
the expiration of the short-dated option, the trader is left with another option
|
||
that may have time value. To estimate what the position will be worth when
|
||
the short-term option expires, the value of the long-term option must be
|
||
analyzed using the greeks. This is true of the variants of the calendar—
|
||
double calendars, diagonals, and double diagonals—as well. This chapter
|
||
will show how to analyze strategies that involve options with different
|
||
expirations and discuss how and when to use them.
|
||
Buying the Calendar
|
||
The calendar spread and all its variations are commonly associated with
|
||
income-generating spreads. Using calendar spreads as income generators is
|
||
popular among retail and professional traders alike. The process involves
|
||
buying a longer-term at-the-money option and selling a shorter-term at-the-
|
||
money (ATM) option. The options must be either both calls or both puts.
|
||
Because this transaction results in a net debit—the longer-term option being
|
||
purchased has a higher premium than the shorter-term option being sold—
|
||
this is referred to as buying the calendar.
|
||
The main intent of buying a calendar spread for income is to profit from
|
||
the positive net theta of the position. Because the shorter-term ATM option
|
||
decays at a faster rate than the longer-term ATM option, the net theta is
|
||
positive. As for most income spreads, the ideal outcome occurs when the
|
||
underlying is at the short strike (in this case, shared strike) when the
|
||
shorter-term option expires. At this strike price, the long option has its
|
||
highest value, while the short option expires without the trader’s getting
|
||
assigned. As long as the underlying remains close to the strike price, the
|
||
value of the spread rises as time passes, because the short option decreases
|
||
in value faster than the long option.
|
||
For example, a trader, Richard, watches Bed Bath & Beyond Inc. (BBBY)
|
||
on a regular basis. Richard believes that Bed Bath & Beyond will trade in a
|
||
range around $57.50 a share (where it is trading now) over the next month.
|
||
Richard buys the January–February 57.50 call calendar for 0.80. Assuming
|
||
January has 25 days until expiration and February has 53 days, Richard will
|
||
execute the following trade:
|
||
Richard’s best-case scenario occurs when the January calls expire at
|
||
expiration and the February calls retain much of their value.
|
||
If Richard created an at-expiration P&(L) diagram for his position, he’d
|
||
have trouble because of the staggered expiration months. A general
|
||
representation would look something like Exhibit 11.1 .
|
||
EXHIBIT 11.1 Bed Bath & Beyond January–February 57.50 calendar.
|
||
The only point on the diagram that is drawn with definitive accuracy is
|
||
the maximum loss to the downside at expiration of the January call. The
|
||
maximum loss if Bed Bath & Beyond falls low enough is 0.80—the debit
|
||
paid for the spread. If Bed Bath & Beyond is below $57.50 at January
|
||
expiration, the January 57.50 call expires worthless, and the February 57.50
|
||
call may or may not have residual value. If Bed Bath & Beyond declines
|
||
enough, the February 57.50 call can lose all of its value, even with residual
|
||
time until expiration. If the stock falls enough, the entire 0.80 debit would
|
||
be a loss.
|
||
If Bed Bath & Beyond is above $57.50 at January expiration, the January
|
||
57.50 call will be trading at parity. It will be a negative-100-delta option,
|
||
imitating short stock. If Bed Bath & Beyond is trading high enough, the
|
||
February 57.50 call will become a positive-100-delta option trading at
|
||
parity plus the interest calculated on the strike. The February deep-in-the-
|
||
money option would imitate long stock. At a 2 percent interest rate, interest
|
||
on the 57.50 strike is about 0.17. Therefore, Richard would essentially have
|
||
a short stock position from $57.50 from the January 57.50 call and would
|
||
be essentially long stock from $57.50 plus 0.28 from the February call. The
|
||
maximum loss to the upside is about 0.63 (0.80 − 0.17).
|
||
The maximum loss if Bed Bath & Beyond is trading over $57.50 at
|
||
expiration is only an estimate that assumes there is no time value and that
|
||
interest and dividends remain constant. Ultimately, the maximum loss will
|
||
be 0.80, the premium paid, if there is no time value or carry considerations.
|
||
The maximum profit is gained if Bed Bath & Beyond is at $57.50 at
|
||
expiration. At this price, the February 57.50 call is worth the most it can be
|
||
worth without having the January 57.50 call assigned and creating negative
|
||
deltas to the upside. But how much precisely is the maximum profit?
|
||
Richard would have to know what the February 57.50 call would be worth
|
||
with Bed Bath & Beyond stock trading at $57.50 at February expiration
|
||
before he can know the maximum profit potential. Although Richard can’t
|
||
know for sure at what price the calls will be trading, he can use a pricing
|
||
model to estimate the call’s value. Exhibit 11.2 shows analytics at January
|
||
expiration.
|
||
EXHIBIT 11.2 Bed Bath & Beyond January–February 57.50 call calendar
|
||
greeks at January expiration.
|
||
With an unchanged implied volatility of 23 percent, an interest rate of two
|
||
percent, and no dividend payable before February expiration, the February
|
||
57.50 calls would be valued at 1.53 at January expiration. In this best-case
|
||
scenario, therefore, the spread would go from 0.80, where Richard
|
||
purchased it, to 1.53, for a gain of 91 percent. At January expiration, with
|
||
Bed Bath & Beyond at $57.50, the January call would expire; thus, the
|
||
spread is composed of just the February 57.50 call.
|
||
Let’s now go back in time and see how Richard figured this trade. Exhibit
|
||
11.3 shows the position when the trade is established.
|
||
EXHIBIT 11.3 Bed Bath & Beyond January–February 57.50 call calendar.
|
||
A small and steady rise in the stock price with enough time to collect
|
||
theta is the recipe for success in this trade. As time passes, delta will flatten
|
||
out if Bed Bath & Beyond is still right at-the-money. The delta of the
|
||
January call that Richard is short will move closer to exactly −0.50. The
|
||
February call delta moves toward exactly +0.50.
|
||
Gamma and theta will both rise if Bed Bath & Beyond stays around the
|
||
strike. As expiration approaches, there is greater risk if there is movement
|
||
and greater reward if there is not.
|
||
Vega is positive because the long-term option with the higher vega is the
|
||
long leg of the spread. When trading calendars for income, implied
|
||
volatility (IV) must be considered as a possible threat. Because it is
|
||
Richard’s objective to profit from Bed Bath & Beyond being at $57.50 at
|
||
expiration, he will try to avoid vega risk by checking that the implied
|
||
volatility of the February call is in the lower third of the 12-month range.
|
||
He will also determine if there are any impending events that could cause
|
||
IV to change. The less likely IV is to drop, the better.
|
||
If there is an increase in IV, that may benefit the profitability of the trade.
|
||
But a rise in IV is not really a desired outcome for two reasons. First, a rise
|
||
in IV is often more pronounced in the front month than in the months
|
||
farther out. If this happens, Richard can lose more on the short call than he
|
||
makes on the long call. Second, a rise in IV can indicate anxiety and
|
||
therefore a greater possibility for movement in the underlying stock.
|
||
Richard doesn’t want IV to rock the boat. “Buy low, stay low” is his credo.
|
||
Rho is positive also. A rise in interest rates benefits the position because
|
||
the long-term call is helped by the rise more than the short call is hurt. With
|
||
only a one-month difference between the two options, rho is very small.
|
||
Overall, rho is inconsequential to this trade.
|
||
There is something curious to note about this trade: the gamma and the
|
||
vega. Calendar spreads are the one type of trade where gamma can be
|
||
negative while vega is positive, and vice versa. While it appears—at least
|
||
on the surface—that Richard wants higher IV, he certainly wants low
|
||
realized volatility.
|
||
Bed Bath & Beyond January–February 57.50 Put
|
||
Calendar
|
||
Richard’s position would be similar if he traded the January–February 57.50
|
||
put calendar rather than the call calendar. Exhibit 11.4 shows the put
|
||
calendar.
|
||
EXHIBIT 11.4 Bed Bath & Beyond January–February 57.50 put calendar.
|
||
The premium paid for the put spread is 0.75. A huge move in either
|
||
direction means a loss. It is about the same gamma/theta trade as the 57.50
|
||
call calendar. At expiration, with Bed Bath & Beyond at $57.50 and IV
|
||
unchanged, the value of the February put would be 1.45—a 93 percent gain.
|
||
The position is almost exactly the same as the call calendar. The biggest
|
||
difference is that the rho is negative, but that is immaterial to the trade. As
|
||
with the call spread, being short the front-month option means negative
|
||
gamma and positive theta; being long the back month means positive vega.
|
||
Managing an Income-Generating
|
||
Calendar
|
||
Let’s say that instead of trading a one-lot calendar, Richard trades it 20
|
||
times. His trade in this case is
|
||
His total cash outlay is $1,600 ($80 times 20). The greeks for this trade,
|
||
listed in Exhibit 11.5 , are also 20 times the size of those in Exhibit 11.3 .
|
||
EXHIBIT 11.5 20-Lot Bed Bath & Beyond January–February 57.50 call
|
||
calendar.
|
||
Note that Richard has a +0.18 delta. This means he’s long the equivalent
|
||
of about 18 shares of stock—still pretty flat. A gamma of −0.72 means that
|
||
if Bed Bath & Beyond moves $1 higher, his delta will be starting to get
|
||
short; and if it moves $1 lower he will be longer, long 90 deltas.
|
||
Richard can use the greeks to get a feel for how much the stock can move
|
||
before negative gamma causes a loss. If Bed Bath & Beyond starts trending
|
||
in either direction, Richard may need to react. His plan is to cover his deltas
|
||
to continue the position.
|
||
Say that after one week Bed Bath & Beyond has dropped $1 to $56.50.
|
||
Richard will have collected seven days of theta, which will have increased
|
||
slightly from $18 per day to $20 per day. His average theta during that time
|
||
is about $19, so Richard’s profit attributed to theta is about $133.
|
||
With a big-enough move in either direction, Richard’s delta will start
|
||
working against him. Since he started with a delta of +0.18 on this 20-lot
|
||
spread and a gamma of −0.72, one might think that his delta would increase
|
||
to 0.90 with Bed Bath & Beyond a dollar lower (18 − [−0.072 × 1.00]). But
|
||
because a week has passed, his delta would actually get somewhat more
|
||
positive. The shorter-term call’s delta will get smaller (closer to zero) at a
|
||
faster rate compared to the longer-term call because it has less time to
|
||
expiration. Thus, the positive delta of the long-term option begins to
|
||
outweigh the negative delta of the short-term option as time passes.
|
||
In this scenario, Richard would have almost broken even because what
|
||
would be lost on stock price movement, is made up for by theta gains.
|
||
Richard can sell about 100 shares of Bed Bath & Beyond to eliminate his
|
||
immediate directional risk and stem further delta losses. The good news is
|
||
that if Bed Bath & Beyond declines more after this hedge, the profit from
|
||
the short stock offsets losses from the long delta. The bad news is that if
|
||
BBBY rebounds, losses from the short stock offset gains from the long
|
||
delta.
|
||
After Richard’s hedge trade is executed, his delta would be zero. His
|
||
other greeks remain unchanged. The idea is that if Bed Bath & Beyond
|
||
stays at its new price level of $56.50, he reaps the benefits of theta
|
||
increasing with time from $18 per day. Richard is accepting the new price
|
||
level and any profits or losses that have occurred so far. He simply adjusts
|
||
his directional exposure to a zero delta.
|
||
Rolling and Earning a “Free” Call
|
||
Many traders who trade income-generating strategies are conservative.
|
||
They are happy to sell low IV for the benefits afforded by low realized
|
||
volatility. This is the problem-avoidance philosophy of trading. Due to risk
|
||
aversion, it’s common to trade calendar spreads by buying the two-month
|
||
option and selling the one-month option. This can allow traders to avoid
|
||
buying the calendar in earnings months, and it also means a shorter time
|
||
horizon, signifying less time for something unwanted to happen.
|
||
But there’s another school of thought among time-spread traders. There
|
||
are some traders who prefer to buy a longer-term option—six months to a
|
||
year—while selling a one-month option. Why? Because month after month,
|
||
the trader can roll the short option to the next month. This is a simple tactic
|
||
that is used by market makers and other professional traders as well as
|
||
savvy retail traders. Here’s how it works.
|
||
XYZ stock is trading at $60 per share. A trader has a neutral outlook over
|
||
the next six months and decides to buy a calendar. Assuming that July has
|
||
29 days until expiration and December has 180, the trader will take the
|
||
following position:
|
||
The initial debit here is 2.55. The goal is basically the same as for any
|
||
time spread: collect theta without negative gamma spoiling the party. There
|
||
is another goal in these trades as well: to roll the spread.
|
||
At the end of month one, if the best-case scenario occurs and XYZ is
|
||
sitting at $60 at July expiration, the July 60 call expires. The December 60
|
||
call will then be worth 3.60, assuming all else is held constant. The positive
|
||
theta of the short July call gives full benefits as the option goes from 1.45 to
|
||
zero. The lower negative theta of the December call doesn’t bite into profits
|
||
quite as much as the theta of a short-term call would.
|
||
The profit after month one is 1.05. Profit is derived from the December
|
||
call, worth 3.60 at July expiry, minus the 2.55 initial spread debit. This
|
||
works out to about a 41 percent return. The profit is hardly as good as it
|
||
would have been if a short-term, less expensive August 60 call were the
|
||
long leg of this spread.
|
||
Rolling the Spread
|
||
The July–December spread is different from short-term spreads, however.
|
||
When the Julys expire, the August options will have 29 days until
|
||
expiration. If volatility is still the same, XYZ is still at $60, and the trader’s
|
||
forecast is still neutral, the 29-day August 60 calls can be sold for 1.45. The
|
||
trader can either wait until the Monday after July expiration and then sell
|
||
the August 60s, or when the Julys are offered at 0.05 or 0.10, he can buy the
|
||
Julys and sell the Augusts as a spread. In either case, it is called rolling the
|
||
spread. When the August expires, he can sell the Septembers, and so on.
|
||
The goal is to get a credit month after month. At some point, the
|
||
aggregate credit from the call sales each month is greater than the price
|
||
initially paid for the long leg of the spread, thus eliminating the original net
|
||
debit. Exhibit 11.6 shows how the monthly credits from selling the one-
|
||
month calls aggregate over time.
|
||
EXHIBIT 11.6 A “free” call.
|
||
After July has expired, 1.45 of premium is earned. After August
|
||
expiration, the aggregate increases to 2.90. When the September calls,
|
||
which have 36 days until expiration, are sold, another 1.60 is added to the
|
||
total premium collected. Over three months—assuming the stock price,
|
||
volatility, and the other inputs don’t change—this trader collects a total of
|
||
4.50. That’s 0.50 more than the price originally paid for the December 60
|
||
call leg of the spread.
|
||
At this point, he effectively owns the December call for free. Of course,
|
||
this call isn’t really free; it’s earned. It’s paid for with risk and maybe a few
|
||
sleepless nights. At this point, even if the stock and, consequently, the
|
||
December call go to zero, the position is still a profitable trade because of
|
||
the continued month-to-month rolling. This is now a no-lose situation.
|
||
When the long call of the spread has been paid for by rolling, there are
|
||
three choices moving forward: sell it, hold it, or continue writing calls
|
||
against it. If the trader’s opinion calls for the stock to decline, it’s logical to
|
||
sell the December call and take the residual value as profit. In this case,
|
||
over three months the trade will have produced 4.50 in premium from the
|
||
sale of three consecutive one-month calls, which is more than the initial
|
||
purchase price of the December call. At September expiration, the premium
|
||
that will be received for selling the December call is all profit, plus 0.50,
|
||
which is the aggregate premium minus the initial cost of the December call.
|
||
If the outlook is for the underlying to rise, it makes sense to hold the call.
|
||
Any appreciation in the value of the call resulting from delta gains as the
|
||
underlying moves higher is good—$0.50 plus whatever the call can be sold
|
||
for.
|
||
If the forecast is for XYZ to remain neutral, it’s logical to continue selling
|
||
the one-month call. Because the December call has been financed by the
|
||
aggregate short call premiums already, additional premiums earned by
|
||
writing calls are profit with “free” protection. As long as the short is closed
|
||
at its expiration, the risk of loss is eliminated.
|
||
This is the general nature of rolling calls in a calendar spread. It’s a
|
||
beautiful plan when it works! The problem is that it is incredibly unlikely
|
||
that the stock will stay right at $60 per share for five months. It’s almost
|
||
inevitable that it will move at some point. It’s like a game of Russian
|
||
roulette. At some point it’s going to be a losing proposition—you just don’t
|
||
know when. The benefit of rolling is that if the trade works out for a few
|
||
months in a row, the long call is paid for and the risk of loss is covered by
|
||
aggregate profits.
|
||
If we step outside this best-case theoretical world and consider what is
|
||
really happening on a day-to-day basis, we can gain insight on how to
|
||
manage this type of trade when things go wrong. Effectively, a long
|
||
calendar is a typical gamma/theta trade. Negative gamma hurts. Positive
|
||
theta helps.
|
||
If we knew which way the stock was going, we would simply buy or sell
|
||
stock to adjust to get long or short deltas. But, unfortunately, we don’t. Our
|
||
only tool is to hedge by buying or selling stock as mentioned above to
|
||
flatten out when gamma causes the position delta to get more positive or
|
||
negative. 1 The bottom line is that if the effect of gamma creates unwanted
|
||
long deltas but the theta/gamma is still a desirable position, selling stock
|
||
flattens out the delta. If the effect of gamma creates unwanted short deltas,
|
||
buying stock flattens out the delta.
|
||
Trading Volatility Term Structure
|
||
There are other reasons for trading calendar spreads besides generating
|
||
income from theta. If there is skew in the term structure of volatility, which
|
||
was discussed in Chapter 3, a calendar spread is a way to trade volatility.
|
||
The tactic is to buy the “cheap” month and sell the “expensive” month.
|
||
Selling the Front, Buying the Back
|
||
If for a particular stock, the February ATM calls are trading at 50 volatility
|
||
and the May ATM calls are trading at 35 volatility, a vol-calendar trader
|
||
would buy the Mays and sell the Februarys. Sounds simple, right? The devil
|
||
is in the details. We’ll look at an example and then discuss some common
|
||
pitfalls with vol-trading calendars.
|
||
George has been studying the implied volatility of a $164.15 stock.
|
||
George notices that front-month volatility has been higher than that of the
|
||
other months for a couple of weeks. There is nothing in the news to indicate
|
||
immediate risk of extraordinary movement occurring in this example.
|
||
George sees that he can sell the 22-day July 165 calls at a 45 percent IV
|
||
and buy the 85-day September 165 calls at a 38 percent IV. George would
|
||
like to buy the calendar spread, because he believes the July ATM volatility
|
||
will drop down to around 38, where the September is trading. If he puts on
|
||
this trade, he will establish the following position:
|
||
What are George’s risks? Because he would be selling the short-term
|
||
ATM option, negative gamma could be a problem. The greeks for this trade,
|
||
shown in Exhibit 11.7 , confirm this. The negative gamma means each
|
||
dollar of stock price movement causes an adverse change of about 0.09 to
|
||
delta. The spread’s delta becomes shorter when the stock rises and longer
|
||
when the stock falls. Because the position’s delta is long 0.369 from the
|
||
start, some price appreciation may be welcomed in the short term. The stock
|
||
advance will yield profits but at a diminishing rate, as negative gamma
|
||
reduces the delta.
|
||
EXHIBIT 11.7 10-lot July–September 165 call calendar.
|
||
But just looking at the net position greeks doesn’t tell the whole story. It
|
||
is important to appreciate the fact that long calendar spreads such as this
|
||
have long vegas. In this case, the vega is +1.522. But what does this number
|
||
really mean? This vega figure means that if IV rises or falls in both the July
|
||
and the September calls by the same amount, the spread makes or loses
|
||
$152 per vol point.
|
||
George’s plan, however, is to see the July’s volatility decline to converge
|
||
with the September’s. He hopes the volatilities of the two months will move
|
||
independently of each other. To better gauge his risk, he needs to look at the
|
||
vega of each option. With the stock at $164.15 the vegas are as follows:
|
||
If George is right and July volatility declines 8 points, from 46 to 38, he
|
||
will make $1,283 ($1.604 × 100 × 8).
|
||
There are a couple of things that can go awry. First, instead of the
|
||
volatilities converging, they can diverge further. Implied volatility is a slave
|
||
to the whims of the market. If the July IV continues to rise while the
|
||
September IV stays the same, George loses $160 per vol point.
|
||
The second thing that can go wrong is the September IV declining along
|
||
with the July IV. This can lead George into trouble, too. It depends the
|
||
extent to which the September volatility declines. In this example, the vega
|
||
of the September leg is about twice that of the July leg. That means that if
|
||
the July volatility loses eight points while the September volatility declines
|
||
four points, profits from the July calls will be negated by losses from the
|
||
September calls. If the September volatility falls even more, the trade is a
|
||
loser.
|
||
IV is a common cause of time-spread failure for market makers. When i
|
||
in the front month rises, the volatility of the back-months sometimes does
|
||
as well. When this happens, it’s often because market makers who sold
|
||
front-month options to retail or institutional buyers buy the back-month
|
||
options to hedge their short-gamma risk. If the market maker buys enough
|
||
back-month options, he or she will accumulate positive vega. But when the
|
||
market sells the front-month volatility back to the market makers, the back
|
||
months drop, too, because market makers no longer need the back months
|
||
for a hedge.
|
||
Traders should study historical implied volatility to avoid this pitfall. As
|
||
is always the case with long vega strategies, there is a risk of a decline in
|
||
IV. Buying long-term options with implied volatility in the lower third of
|
||
the 12-month IV range helps improve the chances of success, since the
|
||
volatility being bought is historically cheap.
|
||
This can be tricky, however. If a trader looks back on a chart of IV for an
|
||
option class and sees that over the past six months it has ranged between 20
|
||
and 30 but nine months ago it spiked up to, say, 55, there must be a reason.
|
||
This solitary spike could be just an anomaly. To eliminate the noise from
|
||
volatility charts, it helps to filter the data. News stories from that time
|
||
period and historical stock charts will usually tell the story of why volatility
|
||
spiked. Often, it is a one-time event that led to the spike. Is it reasonable to
|
||
include this unique situation when trying to get a feel for the typical range
|
||
of implied volatility? Usually not. This is a judgment call that needs to be
|
||
made on a case-by-case basis. The ultimate objective of this exercise is to
|
||
determine: “Is volatility cheap or expensive?”
|
||
Buying the Front, Selling the Back
|
||
All trading is based on the principle of “buy low, sell high”—even volatility
|
||
trading. With time spreads, we can do both at once, but we are not limited
|
||
to selling the front and buying the back. When short-term options are
|
||
trading at a lower IV than long-term ones, there may be an opportunity to
|
||
sell the calendar. If the IV of the front month is 17 and the back-month IV is
|
||
25, for example, it could be a wise trade to buy the front and sell the back.
|
||
But selling time spreads in this manner comes with its own unique set of
|
||
risks.
|
||
First, a short calendar’s greeks are the opposite of those of a long
|
||
calendar. This trade has negative theta with positive gamma. A sideways
|
||
market hurts this position as negative theta does its damage. Each day of
|
||
carrying the position is paid for with time decay.
|
||
The short calendar is also a short-vega trade. At face value, this implies
|
||
that a drop in IV leads to profit and that the higher the IV sold in the back
|
||
month, the better. As with buying a calendar, there are some caveats to this
|
||
logic.
|
||
If there is an across-the-board decline in IV, the net short vega will lead to
|
||
a profit. But an across-the-board drop in volatility, in this case, is probably
|
||
not a realistic expectation. The front month tends to be more sensitive to
|
||
volatility. It is a common occurrence for the front month to be “cheap”
|
||
while the back month is “expensive.”
|
||
The volatilities of the different months can move independently, as they
|
||
can when one buys a time spread. There are a couple of scenarios that might
|
||
lead to the back-month volatility’s being higher than the front month. One is
|
||
high complacency in the short term. When the market collectively sells
|
||
options in expectation of lackluster trading, it generally prefers to sell the
|
||
short-term options. Why? Higher theta. Because the trade has less time until
|
||
expiration, the trade has a shorter period of risk. Because of this, selling
|
||
pressure can push down IV in the front-month options more than in the
|
||
back. Again, the front month is more sensitive to changes in implied
|
||
volatility.
|
||
Because volatility has peaks and troughs, this can be a smart time to sell a
|
||
calendar. The focus here is in seeing the “cheap” front month rise back up
|
||
to normal levels, not so much in seeing the “expensive” back month fall.
|
||
This trade is certainly not without risk. If the market doesn’t move, the
|
||
negative theta of the short calendar leads to a slow, painful death for
|
||
calendar sellers.
|
||
Another scenario in which the back-month volatility can trade higher than
|
||
the front is when the market expects higher movement after the expiration
|
||
of the short-term option but before the expiration of the long-term option.
|
||
Situations such as the expectation of the resolution of a lawsuit, a product
|
||
announcement, or some other one-time event down the road are
|
||
opportunities for the market to expect such movement. This strategy
|
||
focuses on the back-month vol coming back down to normal levels, not on
|
||
the front-month vol rising. This can be a more speculative situation for a
|
||
volatility trade, and more can go wrong.
|
||
The biggest volatility risk in selling a time spread is that what goes up can
|
||
continue to go up. The volatility disparity here is created by hedgers and
|
||
speculators favoring long-term options, hence pushing up the volatility, in
|
||
anticipation of a big future stock move. As the likely date of the anticipated
|
||
event draws near, more buyers can be attracted to the market, driving up IV
|
||
even further. Realized volatility can remain low as investors and traders lie
|
||
in wait. This scenario is doubly dangerous when volatility rises and the
|
||
stock doesn’t move. A trader can lose on negative theta and lose on negative
|
||
vega.
|
||
A Directional Approach
|
||
Calendar spreads are often purchased when the outlook for the underlying is
|
||
neutral. Sell the short-term ATM option; buy the long-term ATM option;
|
||
collect theta. But with negative gamma, these trades are never really
|
||
neutral. The delta is constantly changing, becoming more positive or
|
||
negative. It’s like a rubber band: at times being stretched in either direction
|
||
but always demanding a pull back to the strike. When the strike price being
|
||
traded is not ATM, calendar spreads can be strategically traded as
|
||
directional plays.
|
||
Buying a calendar, whether using calls or puts, where the strike price is
|
||
above the current stock price is a bullish strategy. With calls, the positive
|
||
delta of the long-term out-of-the-money (OTM) call will be greater than the
|
||
negative delta of the short-term OTM call. For puts, the positive delta of the
|
||
short-term in-the-money (ITM) put will be greater than the negative delta of
|
||
the long-term ITM put.
|
||
Just the opposite applies if the strike price is below the current stock
|
||
price. The negative delta of the short-term ITM call is greater than the
|
||
positive delta of the long-term ITM call. The negative delta of the long-term
|
||
OTM put is greater than the positive delta of the short-term OTM put.
|
||
When the position starts out with either a positive or negative delta,
|
||
movement in the direction of the delta is necessary for the trade to be
|
||
profitable. Negative gamma is also an important strategic consideration.
|
||
Stock-price movement is needed, but not too much.
|
||
Buying calendar spreads is like playing outfield in a baseball game. To
|
||
catch a fly ball, an outfielder must focus on both distance and timing. He
|
||
must gauge how far the ball will be hit and how long it will take to get
|
||
there. With calendars, the distance is the strike price—that’s where the stock
|
||
needs to be—and the time is the expiration day of the short month’s option:
|
||
that’s when it needs to be at the target price.
|
||
For example, with Wal-Mart (WMT) at $48.50, a trader, Pete, is looking
|
||
for a rise to about $50 over the next five or six weeks. Pete buys the
|
||
August–September call calendar. In this example, August has 39 days until
|
||
expiration and September has 74 days.
|
||
Exactly what does 50 cents buy Pete? The stock price sitting below the
|
||
strike price means a net positive delta. This long time spread also has
|
||
positive theta and vega. Gamma is negative. Exhibit 11.8 shows the
|
||
specifics.
|
||
EXHIBIT 11.8 10-lot Wal-Mart August–September 50 call calendar.
|
||
The delta of this trade, while positive, is relatively small with 39 days left
|
||
until August expiration. It’s not rational to expect a quick profit if the stock
|
||
advances faster than expected. But ultimately, a rise in stock price is the
|
||
goal. In this example, Wal-Mart needs to rise to $50, and timing is
|
||
everything. It needs to be at that price in 39 days. In the interim, a move too
|
||
big and too fast in either direction hurts the trade because of negative
|
||
gamma. Starting with Wal-Mart at $48.50, delta/gamma problems are worse
|
||
to the downside. Exhibit 11.9 shows the effects of stock price on delta,
|
||
gamma, and theta.
|
||
EXHIBIT 11.9 Stock price movement and greeks.
|
||
If Wal-Mart moves lower, the delta gets more positive, racking up losses
|
||
at a higher rate. To add to Pete’s woes, theta becomes less of a benefit as the
|
||
stock drifts lower. At $47 a share, theta is about flat. With Wal-Mart trading
|
||
even lower than $47, the positive theta of the August call is overshadowed
|
||
by the negative theta of the September. Theta can become negative, causing
|
||
the position to lose value as time passes.
|
||
A big move to the upside doesn’t help either. If Wal-Mart rises just a bit,
|
||
the −0.323 gamma only lessens the benefit of the 0.563 delta. But above
|
||
$50, negative gamma begins to cause the delta to become increasingly
|
||
negative. Theta begins to wither away at higher stock prices as well.
|
||
The place to be is right at $50. The delta is flat and theta is highest. As
|
||
long as Wal-Mart finds its way up to this price by the third Friday of
|
||
August, life is good for Pete.
|
||
The In-or-Out Crowd
|
||
Pete could just as well have traded the Aug–Sep 50 put calendar in this
|
||
situation. If he’d been bearish, he could have traded either the Aug–Sep 45
|
||
call spread or the Aug–Sep 45 put spread. Whether bullish or bearish, as
|
||
mentioned earlier, the call calendar and the put calendar both function about
|
||
the same. When deciding which to use, the important consideration is that
|
||
one of them will be in-the-money and the other will be OTM. Whether you
|
||
have an ITM spread or an OTM spread has potential implications for the
|
||
success of the trade.
|
||
The bid-ask spreads tend to be wider for higher-delta, ITM options.
|
||
Because of this, it can be more expensive to enter into an ITM calendar.
|
||
Why? Trading options with wider markets requires conceding more edge.
|
||
Take the following options series:
|
||
By buying the May 50 calls at 3.20, a trader gives up 0.10 of theoretical
|
||
edge (3.20 is 0.10 higher than the theoretical value). Buying the put at 1.00
|
||
means buying only 0.05 over theoretical.
|
||
Because a calendar is a two-legged spread, the double edge given up by
|
||
trading the wider markets of two in-the-money options can make the out-of-
|
||
the-money spread a more attractive trade. The issue of wider markets is
|
||
compounded when rolling the spread. Giving up a nickel or a dime each
|
||
month can add up, especially on nominally low-priced spreads. It can cut
|
||
into a high percentage of profits.
|
||
Early assignment can complicate ITM calendars made up of American
|
||
options, as dividends and interest can come into play. The short leg of the
|
||
spread could get assigned before the expiration date as traders exercise calls
|
||
to capture the dividend. Short ITM puts may get assigned early because of
|
||
interest.
|
||
Although assignment is an undesirable outcome for most calendar spread
|
||
traders, getting assigned on the short leg of the calendar spread may not
|
||
necessarily create a significantly different trade. If a long put calendar, for
|
||
example, has a short front-month put that is so deep in-the-money that it is
|
||
likely to get assigned, it is trading close to a 100 delta. It is effectively a
|
||
long stock position already. After assignment, when a long stock position is
|
||
created, the resulting position is long stock with a deep ITM long put—a
|
||
fairly delta-flat position.
|
||
Double Calendars
|
||
Definition : A double calendar spread is the execution of two calendar
|
||
spreads that have the same months in common but have two different strike
|
||
prices.
|
||
Example
|
||
Sell 1 XYZ February 70 call
|
||
Buy 1 XYZ March 70 call
|
||
Sell 1 XYZ February 75 call
|
||
Buy 1 XYZ March 75 call
|
||
Double calendars can be traded for many reasons. They can be vega
|
||
plays. If there is a volatility-time skew, a double calendar is a way to take a
|
||
position without concentrating delta or gamma/theta risk at a single strike.
|
||
This spread can also be a gamma/theta play. In that case, there are two
|
||
strikes, so there are two potential focal points to gravitate to (in the case of
|
||
a long double calendar) or avoid (in the case of a short double calendar).
|
||
Selling the two back-month strikes and buying the front-month strikes
|
||
leads to negative theta and positive gamma. The positive gamma creates
|
||
favorable deltas when the underlying moves. Positive or negative deltas can
|
||
be covered by trading the underlying stock. With positive gamma, profits
|
||
can be racked up by buying the underlying to cover short deltas and
|
||
subsequently selling the underlying to cover long deltas.
|
||
Buying the two back-month strikes and selling the front-month strikes
|
||
creates negative gamma and positive theta, just as in a conventional
|
||
calendar. But the underlying stock has two target price points to shoot for at
|
||
expiration to achieve the maximum payout.
|
||
Often double calendars are traded as IV plays. Many times when they are
|
||
traded as IV plays, traders trade the lower-strike spread as a put calendar
|
||
and the higher-strike spread a call calendar. In that case, the spread is
|
||
sometimes referred to as a strangle swap . Strangles are discussed in
|
||
Chapter 15.
|
||
Two Courses of Action
|
||
Although there may be many motivations for trading a double calendar,
|
||
there are only two courses of action: buy it or sell it. While, for example,
|
||
the trader’s goal may be to capture theta, buying a double calendar comes
|
||
with the baggage of the other greeks. Fully understanding the
|
||
interrelationship of the greeks is essential to success. Option traders must
|
||
take a holistic view of their positions.
|
||
Let’s look at an example of buying a double calendar. In this example,
|
||
Minnesota Mining & Manufacturing (MMM) has been trading in a range
|
||
between about $85 and $97 per share. The current price of Minnesota
|
||
Mining & Manufacturing is $87.90. Economic data indicate no specific
|
||
reasons to anticipate that Minnesota Mining & Manufacturing will deviate
|
||
from its recent range over the next month—that is, there is nothing in the
|
||
news, no earnings anticipated, and the overall market is stable. August IV is
|
||
higher than October IV by one volatility point, and October implied
|
||
volatility is in line with 30-day historical volatility. There are 38 days until
|
||
August expiration, and 101 days until October expiration.
|
||
The Aug–Oct 85–90 double calendar can be traded at the following
|
||
prices:
|
||
Much like a traditional calendar spread, the price points cannot be
|
||
definitively plotted on a P&(L) diagram. What is known for certain is that at
|
||
August expiration, the maximum loss is $3,200. While it’s comforting to
|
||
know that there is limited loss, losing the entire premium that was paid for
|
||
the spread is an outcome most traders would like to avoid. We also know
|
||
the maximum gains occur at the strike prices; but not exactly what the
|
||
maximum profit can be. Exhibit 11.10 provides an alternative picture of the
|
||
position that is useful in managing the trade on a day-to-day basis.
|
||
EXHIBIT 11.10 10-lot Minnesota Mining & Manufacturing Aug–Oct 85–
|
||
90 double call calendar.
|
||
These numbers are a good representation of the position’s risk. Knowing
|
||
that long calendars and long double calendars have maximum losses at the
|
||
expiration of the short-term option equal to the net premiums paid, the max
|
||
loss in this example is 3.20. Break-even prices are not relevant to this
|
||
position because they cannot be determined with any certainty. What is
|
||
important is to get a feel for how much movement can hurt the position.
|
||
To make $19 a day in theta, a −0.468 gamma must be accepted. In the
|
||
long run, $1 of movement is irrelevant. In fact, some movement is favorable
|
||
because the ideal point for MMM to be at, at August expiration is either $85
|
||
or $90. So while small moves are acceptable, big moves are of concern. The
|
||
negative gamma is an illustration of this warning.
|
||
The other risk besides direction is vega. A positive 1.471 vega means the
|
||
calendar makes or loses about $147 with each one-point across-the-board
|
||
change in implied volatility. Implied volatility is a risk in all calendar
|
||
trades. Volatility was one of the criteria studied when considering this trade.
|
||
Recall that the August IV was one point higher than the October and that
|
||
the October IV was in line with the 30-day historical volatility at inception
|
||
of the trade.
|
||
Considering the volatility data is part of the due diligence when
|
||
considering a calendar or a double calendar. First, the (slightly) more
|
||
expensive options (August) are being sold, and the cheaper ones are being
|
||
bought (October). A study of the company reveals no news to lead one to
|
||
believe that Minnesota Mining & Manufacturing should move at a higher
|
||
realized volatility than it currently is in this example. Therefore, the front
|
||
month’s higher IV is not a red flag. Because the volatility of the October
|
||
option (the month being purchased) is in line with the historical volatility,
|
||
the trader could feel that he is paying a reasonable price for this volatility.
|
||
In the end, the trade is evaluated on the underlying stock, realized
|
||
volatility, and IV. The trade should be executed only after weighing all the
|
||
available data. Trading is both cerebral and statistical in nature. It’s about
|
||
gaining a statistically better chance of success by making rational decisions.
|
||
Diagonals
|
||
Definition : A diagonal spread is an option strategy that involves buying one
|
||
option and selling another option with a different strike price and with a
|
||
different expiration date. Diagonals are another strategy in the time spread
|
||
family.
|
||
Diagonals enable a trader to exploit opportunities similar to those
|
||
exploited by a calendar spread, but because the options in a diagonal spread
|
||
have two different strike prices, the trade is more focused on delta. The
|
||
name diagonal comes from the fact that the spread is a combination of a
|
||
horizontal spread (two different months) and a vertical spread (two different
|
||
strikes).
|
||
Say it’s 22 days until January expiration and 50 days until February
|
||
expiration. Apple Inc. (AAPL) is trading at $405.10. Apple has been in an
|
||
uptrend heading toward the peak of its six-month range, which is around
|
||
$420. A trader, John, believes that it will continue to rise and hit $420 again
|
||
by February expiration. Historical volatility is 28 percent. The February 400
|
||
calls are offered at a 32 implied volatility and the January 420 calls are bid
|
||
on a 29 implied volatility. John executes the following diagonal:
|
||
Exhibit 11.11 shows the analytics for this trade.
|
||
EXHIBIT 11.11 Apple January–February 400–420 call diagonal.
|
||
|
||
From the presented data, is this a good trade? The answer to this question
|
||
is contingent on whether the position John is taking is congruent with his
|
||
view of direction and volatility and what the market tells him about these
|
||
elements.
|
||
John is bullish up to August expiration, and the stock in this example is in
|
||
an uptrend. Any rationale for bullishness may come from technical or
|
||
fundamental analysis, but techniques for picking direction, for the most
|
||
part, are beyond the scope of this book. Buying the lower strike in the
|
||
February option gives this trade a more positive delta than a straight
|
||
calendar spread would have. The trader’s delta is 0.255, or the equivalent of
|
||
about 25.5 shares of Apple. This reflects the trader’s directional view.
|
||
The volatility is not as easy to decipher. A specific volatility forecast was
|
||
not stated above, but there are a few relevant bits of information that should
|
||
be considered, whether or not the trader has a specific view on future
|
||
volatility. First, the historical volatility is 28 percent. That’s lower than
|
||
either the January or the February calls. That’s not ideal. In a perfect world,
|
||
it’s better to buy below historical and sell above. To that point, the February
|
||
option that John is buying has a higher volatility than the January he is
|
||
selling. Not so good either. Are these volatility observations deal breakers?
|
||
A Good Ex-Skews
|
||
It’s important to take skew into consideration. Because the January calls
|
||
have a higher strike price than the February calls, it’s logical for them to
|
||
trade at a lower implied volatility. Is this enough to justify the possibility of
|
||
selling the lower volatility? Consider first that there is some margin for
|
||
error. The bid-ask spreads of each of the options has a volatility disparity. In
|
||
this case, both the January and February calls are 10 cents wide. That means
|
||
with a January vega of 0.34 the bid-ask is about 0.29 vol points wide. The
|
||
Februarys have a 0.57 vega. They are about 0.18 vol points wide. That
|
||
accounts for some of the disparity. Natural vertical skew accounts for the
|
||
rest of the difference, which is acceptable as long as the skew is not
|
||
abnormally pronounced.
|
||
As for other volatility considerations, this diagonal has the rather
|
||
unorthodox juxtaposition of positive vega and negative gamma seen with
|
||
other time spreads. The trader is looking for a move upward, but not a big
|
||
one. As the stock rises and Apple moves closer to the 420 strike, the
|
||
positive delta will shrink and the negative gamma will increase. In order to
|
||
continue to enjoy profits as the stock rises, John may have to buy shares of
|
||
Apple to keep his positive delta. The risk here is that if he buys stock and
|
||
Apple retraces, he may end up negative scalping stock. In other words, he
|
||
may sell it back at a lower price than he bought it. Using stock to adjust the
|
||
delta in a negative-gamma play can be risky business. Gamma scalping is
|
||
addressed further in Chapter 13.
|
||
Making the Most of Your Options
|
||
The trader from the previous example had a time-spread alternative to the
|
||
diagonal: John could have simply bought a traditional time spread at the
|
||
420 strike. Recall that calendars reap the maximum reward when they are at
|
||
the shared strike price at expiration of the short-term option. Why would he
|
||
choose one over the other?
|
||
The diagonal in that example uses a lower-strike call in the February than
|
||
a straight 420 calendar spread and therefore has a higher delta, but it costs
|
||
more. Gamma, theta, and vega may be slightly lower with the in-the-money
|
||
call, depending on how far from the strike price the ITM call is and how
|
||
much time until expiration it has. These, however, are less relevant
|
||
differences.
|
||
The delta of the February 400 call is about 0.57. The February 420 call,
|
||
however, has only a 0.39 delta. The 0.18 delta difference between the calls
|
||
means the position delta of the time spread will be only about 0.07 instead
|
||
of about 0.25 of the diagonal—a big difference. But the trade-off for lower
|
||
delta is that the February 420 call can be bought for 12.15. That means a
|
||
lower debit paid—that means less at risk. Conversely, though there is
|
||
greater risk with the diagonal, the bigger delta provides a bigger payoff if
|
||
the trader is right.
|
||
Double Diagonals
|
||
A double diagonal spread is the simultaneous trading of two diagonal
|
||
spreads: one call spread and one put spread. The distance between the
|
||
strikes is the same in both diagonals, and both have the same two expiration
|
||
months. Usually, the two long-term options are more out-of-the-money than
|
||
the two shorter-term options. For example
|
||
Buy 1 XYZ May 70 put
|
||
Sell 1 XYZ March 75 put
|
||
Sell 1 XYZ March 85 call
|
||
Buy 1 XYZ May 90 call
|
||
Like many option strategies, the double diagonal can be looked at from a
|
||
number of angles. Certainly, this is a trade composed of two diagonal
|
||
spreads—the March–May 70–75 put and the March–May 85–90 call. It is
|
||
also two strangles—buying the May 70–90 strangle and selling the March
|
||
75–85 strangle. One insightful way to look at this spread is as an iron
|
||
condor in which the guts are March options and the wings are May options.
|
||
Trading a double diagonal like this one, rather than a typically positioned
|
||
iron condor, can offer a few advantages. The first advantage, of course, is
|
||
theta. Selling short-term options and buying long-term options helps the
|
||
trader reap higher rates of decay. Theta is the raison d’être of the iron
|
||
condor. A second advantage is rolling. If the underlying asset stays in a
|
||
range for a long period of time, the short strangle can be rolled month after
|
||
month. There may, in some cases, also be volatility-term-structure
|
||
discrepancies on which to capitalize.
|
||
A trader, Paul, is studying JPMorgan (JPM). The current stock price is
|
||
$49.85. In this example, JPMorgan has been trading in a pretty tight range
|
||
over the past few months. Paul believes it will continue to do so over the
|
||
next month. Paul considers the following trade:
|
||
|
||
Paul considers volatility. In this example, the JPMorgan ATM call, the
|
||
August 50 (which is not shown here), is trading at 22.9 percent implied
|
||
volatility. This is in line with the 20-day historical volatility, which is 23
|
||
percent. The August IV appears to be reasonably in line with the September
|
||
volatility, after accounting for vertical skew. The IV of the August 52.50
|
||
calls is 1.5 points above that of the September 55 calls and the August 47.50
|
||
put IV is 1.6 points below the September 45 put IV. It appears that neither
|
||
month’s volatility is cheap or expensive.
|
||
Exhibit 11.12 shows the trade’s greeks.
|
||
EXHIBIT 11.12 10-lot JPMorgan August–September 45–47.50–52.50–55
|
||
double diagonal.
|
||
The analytics of this trade are similar to those of an iron condor.
|
||
Immediate directional risk is almost nonexistent, as indicated by the delta.
|
||
But gamma and theta are high, even higher than they would be if this were
|
||
a straight September iron condor, although not as high as if this were an
|
||
August iron condor.
|
||
Vega is positive. Surely, if this were an August or a September iron
|
||
condor, vega would be negative. In this example, Paul is indifferent as to
|
||
whether vega is positive or negative because IV is fairly priced in terms of
|
||
historical volatility and term structure. In fact, to play it close to the vest,
|
||
Paul probably wants the smallest vega possible, in case of an IV move.
|
||
Why take on the risk?
|
||
The motivation for Paul’s double diagonal was purely theta. The
|
||
volatilities were all in line. And this one-month spread can’t be rolled. If
|
||
Paul were interested in rolling, he could have purchased longer-term
|
||
options. But if he is anticipating a sideways market for only the next month
|
||
and feels that volatility could pick up after that, the one-month play is the
|
||
way to go. After August expiration, Paul will have three choices: sell his
|
||
Septembers, hold them, or turn them into a traditional iron condor by
|
||
selling the September 47.50s and 52.50s. This depends on whether he is
|
||
indifferent, expects high volatility, or expects low volatility.
|
||
The Strength of the Calendar
|
||
Spreads in the calendar-spread family allow traders to take their trading to a
|
||
higher level of sophistication. More basic strategies, like vertical spreads
|
||
and wing spreads, provide a practical means for taking positions in
|
||
direction, realized volatility, and to some extent implied volatility. But
|
||
because calendar-family spreads involve two expiration months, traders can
|
||
take positions in the same market variables as with these more basic
|
||
strategies and also in the volatility spread between different expiration
|
||
months. Calendar-family spreads are veritable volatility spreads. This is a
|
||
powerful tool for option traders to have at their disposal.
|
||
Note
|
||
1 . Advanced hedging techniques are discussed in subsequent chapters.
|
||
PART III
|
||
Volatility
|
||
CHAPTER 12
|
||
Delta-Neutral Trading
|
||
Trading Implied Volatility
|
||
Many of the strategies covered so far have been option-selling strategies.
|
||
Some had a directional bias; some did not. Most of the strategies did have a
|
||
primary focus on realized volatility—especially selling it. These short
|
||
volatility strategies require time. The reward of low stock volatility is theta.
|
||
In general, most of the strategies previously covered were theta trades in
|
||
which negative gamma was an unpleasant inconvenience to be dealt with.
|
||
Moving forward, much of the remainder of this book will involve more
|
||
in-depth discussions of trading both realized and implied volatility (IV),
|
||
with a focus on the harmonious, and sometimes disharmonious, relationship
|
||
between the two types. Much attention will be given to how IV trades in the
|
||
option market, describing situations in which volatility moves are likely to
|
||
occur and how to trade them.
|
||
Direction Neutral versus Direction
|
||
Indifferent
|
||
In the world of nonlinear trading, there are two possible nondirectional
|
||
views of the underlying asset: direction neutral and direction indifferent.
|
||
Direction neutral means the trader believes the stock will not trend either
|
||
higher or lower. The trader is neutral in his or her assessment of the future
|
||
direction of the asset. Short iron condors, long time spreads, and out-of-the-
|
||
money (OTM) credit spreads are examples of direction-neutral strategies.
|
||
These strategies generally have deltas close to zero. Because of negative
|
||
gamma, movement is the bane of the direction-neutral trade.
|
||
Direction indifferent means the trader may desire movement in the
|
||
underlying but is indifferent as to whether that movement is up or down.
|
||
Some direction-indifferent trades are almost completely insulated from
|
||
directional movement, with a focus on interest or dividends instead.
|
||
Examples of these types of trades are conversions, reversals, and boxes,
|
||
which are described in Chapter 6, as well as dividend plays, which are
|
||
described in Chapter 8.
|
||
Other direction-indifferent strategies are long option strategies that have
|
||
positive gamma. In these trades, the focus is on movement, but the direction
|
||
of that movement is irrelevant. These are plays that are bullish on realized
|
||
volatility. Yet other direction-indifferent strategies are volatility plays from
|
||
the perspective of IV. These are trades in which the trader’s intent is to take
|
||
a bullish or bearish position in IV.
|
||
Delta Neutral
|
||
To be truly direction neutral or direction indifferent means to have a delta
|
||
equal to zero. In other words, there are no immediate gains if the underlying
|
||
moves incrementally higher or lower. This zero-delta method of trading is
|
||
called delta-neutral trading .
|
||
A delta-neutral position can be created from any option position simply
|
||
by trading stock to flatten out the delta. A very basic example of a delta-
|
||
neutral trade is a long at-the-money (ATM) call with short stock.
|
||
Consider a trade in which we buy 20 ATM calls that have a 50 delta and
|
||
sell stock on a delta-neutral ratio.
|
||
Buy 20 50-delta calls (long 1,000 deltas)
|
||
Short 1,000 shares (short 1,000 deltas)
|
||
In this position, we are long 1,000 deltas from the calls (20 × 50) and
|
||
short 1,000 deltas from the short sale of stock. The net delta of the position
|
||
is zero. Therefore, the immediate directional exposure has been eliminated
|
||
from the trade. But intuitively, there are other opportunities for profit or loss
|
||
with this trade.
|
||
The addition of short stock to the calls will affect only the delta, not the
|
||
other greeks. The long calls have positive gamma, negative theta, and
|
||
positive vega. Exhibit 12.1 is a simplified representation of the greeks for
|
||
this trade.
|
||
EXHIBIT 12.1 20-lot delta-neutral long call.
|
||
With delta not an immediate concern, the focus here is on gamma, theta,
|
||
and vega. The +1.15 vega indicates that each one-point change in IV makes
|
||
or loses $115 for this trade. Yet there is more to the volatility story. Each
|
||
day that passes costs the trader $50 in time decay. Holding the position for
|
||
an extended period of time can produce a loser even if IV rises. Gamma is
|
||
potentially connected to the success of this trade, too. If the underlying
|
||
moves in either direction, profit from deltas created by positive gamma may
|
||
offset the losses from theta. In fact, a big enough move in either direction
|
||
can produce a profitable trade, regardless of what happens to IV.
|
||
Imagine, for a moment, that this trade is held until expiration. If the stock
|
||
is below the strike price at this point, the calls expire. The resulting position
|
||
is short 1,000 shares of stock. If the stock is above the strike price at
|
||
expiration, the calls can be exercised, creating 2,000 shares of long stock.
|
||
Because the trade is already short 1,000 shares, the resulting net position is
|
||
long 1,000 shares (2,000 − 1,000). Clearly, the more the underlying stock
|
||
moves in either direction the greater the profit potential. The underlying has
|
||
to move far enough above or below the strike price to allow the beneficial
|
||
gains from buying or selling stock to cover the option premium lost from
|
||
time decay. If the trade is held until expiration, the underlying needs to
|
||
move far enough to cover the entire premium spent on the calls.
|
||
The solid lines forming a V in Exhibit 12.2 conceptually illustrate the
|
||
profit or loss for this delta-neutral long call at expiration.
|
||
EXHIBIT 12.2 Profit-and-loss diagram for delta-neutral long-call trade.
|
||
Because of gamma, some deltas will be created by movement of the
|
||
underlying before expiration. Gamma may lead to this being a profitable
|
||
trade in the short term, depending on time and what happens with IV. The
|
||
dotted line illustrates the profit or loss of this trade at the point in time when
|
||
the trade is established. Because the options may still have time value at
|
||
this point—depending on how far from the strike price the stock is trading
|
||
—the value of the position, as a whole, is higher than it will be if the calls
|
||
are trading at parity at expiration. Regardless, the plan is for the stock to
|
||
make a move in either direction. The bigger the move and the faster it
|
||
happens, the better.
|
||
Why Trade Delta Neutral?
|
||
A few years ago, I was teaching a class on option trading. Before the
|
||
seminar began, I was talking with one of the students in attendance. I asked
|
||
him what he hoped to learn in the class. He said that he was really
|
||
interested in learning how to trade delta neutral. When I asked him why he
|
||
was interested in that specific area of trading, he replied, “I hear that’s
|
||
where all the big money is made!”
|
||
This observation, right or wrong, probably stems from the fact that in the
|
||
past most of the trading in this esoteric discipline has been executed by
|
||
professional traders. There are two primary reasons why the pros have
|
||
dominated this strategy: high commissions and high margin requirements
|
||
for retail traders. Recently, these two reasons have all but evaporated.
|
||
First, the ultracompetitive world of online brokers has driven
|
||
commissions for retail traders down to, in some cases, what some market
|
||
makers pay. Second, the oppressive margin requirements that retail option
|
||
traders were subjected to until 2007 have given way to portfolio margining.
|
||
Portfolio Margining
|
||
Customer portfolio margining is a method of calculating customer margin
|
||
in which the margin requirement is based on the “up and down risk” of the
|
||
portfolio. Before the advent of portfolio margining, retail traders were
|
||
subject to strategy-based margining, also called Reg. T margining, which in
|
||
many cases required a significantly higher amount of capital to carry a
|
||
position than portfolio margining does.
|
||
With portfolio margining, highly correlated securities can be offset
|
||
against each other for purposes of calculating margin. For example, SPX
|
||
options and SPY options—both option classes based on the Standard &
|
||
Poor’s 500 Index—can be considered together in the margin calculation. A
|
||
bearish position in one and a bullish position in the other may partially
|
||
offset the overall risk of the portfolio and therefore can help to reduce the
|
||
overall margin requirement.
|
||
With portfolio margining, many strategies are margined in such a way
|
||
that, from the point of view of this author, they are subject to a much more
|
||
logical means of risk assessment. Strategy-based margining required traders
|
||
of some strategies, like a protective put, to deposit significantly more
|
||
capital than one could possibly lose by holding the position. The old rules
|
||
require a minimum margin of 50 percent of the stock’s value and up to 100
|
||
percent of the put premium. A portfolio-margined protective put may
|
||
require only a fraction of what it would with strategy-based margining.
|
||
Even though Reg. T margining is antiquated and sometimes unreasonable,
|
||
many traders must still abide by these constraints. Not all traders meet the
|
||
eligibility requirements to qualify for portfolio-based margining. There is a
|
||
minimum account balance for retail traders to be eligible for this treatment.
|
||
A broker may also require other criteria to be met for the trader to benefit
|
||
from this special margining. Ultimately, portfolio margining allows retail
|
||
traders to be margined similarly to professional traders.
|
||
There are some traders, both professional and otherwise, who indeed have
|
||
made “big money,” as the student in my class said, trading delta neutral.
|
||
But, to be sure, there are successful and unsuccessful traders in many areas
|
||
of trading. The real motivation for trading delta neutral is to take a position
|
||
in volatility, both implied and realized.
|
||
Trading Implied Volatility
|
||
With a typical option, the sensitivity of delta overshadows that of vega. To
|
||
try and profit from a rise or fall in IV, one has to trade delta neutral to
|
||
eliminate immediate directional sensitivity. There are many strategies that
|
||
can be traded as delta-neutral IV strategies simply by adding stock.
|
||
Throughout this chapter, I will continue using a single option leg with
|
||
stock, since it provides a simple yet practical example. It’s important to note
|
||
that delta-neutral trading does not refer to a specific strategy; it refers to the
|
||
fact that the trader is indifferent to direction. Direction isn’t being traded,
|
||
volatility is.
|
||
Volatility trading is fundamentally different from other types of trading.
|
||
While stocks can rise to infinity or decline to zero, volatility can’t. Implied
|
||
volatility, in some situations, can rise to lofty levels of 100, 200, or even
|
||
higher. But in the long-run, these high levels are not sustainable for most
|
||
stocks. Furthermore, an IV of zero means that the options have no extrinsic
|
||
value at all. Now that we have established that the thresholds of volatility
|
||
are not as high as infinity and not as low as zero, where exactly are they?
|
||
The limits to how high or low IV can go are not lines in the sand. They are
|
||
more like tides that ebb and flow, but normally come up only so far onto the
|
||
beach.
|
||
The volatility of an individual stock tends to trade within a range that can
|
||
be unique to that particular stock. This can be observed by studying a chart
|
||
of recent volatility. When IV deviates from the range, it is typical for it to
|
||
return to the range. This is called reversion to the mean , which was
|
||
discussed in Chapter 3. IV can get stretched in either direction like a rubber
|
||
band but then tends to snap back to its original shape.
|
||
There are many examples of situations where reversion to the mean enters
|
||
into trading. In some, volatility temporarily dips below the typical range,
|
||
and in some, it rises beyond the recent range. One of the most common
|
||
examples is the rush and the crush.
|
||
The Rush and the Crush
|
||
In this situation, volatility rises before and falls after a widely anticipated
|
||
news announcement, of earnings, for instance, or of a Food and Drug
|
||
Administration (FDA) approval. In this situation, option buyers rush in and
|
||
bid up IV. The more uncertainty—the more demand for insurance—the
|
||
higher vol rises. When the event finally occurs and the move takes place or
|
||
doesn’t, volatility gets crushed. The crush occurs when volatility falls very
|
||
sharply—sometimes 10 points, 20 points, or more—in minutes. Traders
|
||
with large vega positions appreciate the appropriateness of the term crush
|
||
all too well. Volatility traders also affectionately refer to this sudden drop in
|
||
IV by saying that volatility has gotten “whacked.”
|
||
In order to have a feel for whether implied volatility is high or low for a
|
||
particular stock, you need to know where it’s been. It’s helpful to have an
|
||
idea of where realized volatility is and has been, too. To be sure, one
|
||
analysis cannot be entirely separate from the other. Studying both implied
|
||
and realized volatility and how they relate is essential to seeing the big
|
||
picture.
|
||
The Inertia of Volatility
|
||
Sir Isaac Newton said that an object in motion tends to stay in motion
|
||
unless acted upon by another force. Volatility acts much the same way.
|
||
Most stocks tend to trade with a certain measurable amount of daily price
|
||
fluctuations. This can be observed by looking at the stock’s realized
|
||
volatility. If there is no outside force—some pivotal event that
|
||
fundamentally changes how the stock is likely to behave—one would
|
||
expect the stock to continue trading with the same level of daily price
|
||
movement. This means IV (the market’s expectation of future stock
|
||
volatility) should be the same as realized volatility (the calculated past stock
|
||
volatility).
|
||
But just as in physics, it seems there is always some friction affecting the
|
||
course of what is in motion. Corporate earnings, Federal Reserve Board
|
||
reports, apathy, lulls in the market, armed conflicts, holidays, rumors, and
|
||
takeovers, among other market happenings all provide a catalyst for
|
||
volatility changes. Divergences of realized and implied volatility, then, are
|
||
commonplace. These divergences can create tradable conditions, some of
|
||
which are more easily exploited than others.
|
||
To find these opportunities, a trader must conduct a study of volatility.
|
||
Volatility charts can help a trader visualize the big picture. This historical
|
||
information offers a comparison of what is happening now in volatility with
|
||
what has happened in the past. The following examples use a volatility
|
||
chart to show how two different traders might have traded the rush and
|
||
crush of an earnings report.
|
||
Volatility Selling
|
||
Susie Seller, a volatility trader, studies semiconductor stocks. Exhibit 12.3
|
||
shows the volatilities of a $50 chip stock. The circled area shows what
|
||
happened before and after second-quarter earnings were reported in July.
|
||
The black line is the IV, and the gray is the 30-day historical.
|
||
EXHIBIT 12.3 Chip stock volatility before and after earnings reports.
|
||
Source : Chart courtesy of iVolatility.com
|
||
In mid-July, Susie did some digging to learn that earnings were to be
|
||
announced on July 24, after the close. She was careful to observe the classic
|
||
rush and crush that occurred to varying degrees around the last three
|
||
earnings announcements, in October, January, and April. In each case, IV
|
||
firmed up before earnings only to get crushed after the report. In mid-to-late
|
||
July, she watched as IV climbed to the mid-30s (the rush) just before
|
||
earnings. As the stock lay in wait for the report, trading came to a
|
||
proverbial screeching halt, sending realized volatility lower, to about 13
|
||
percent. Susie waited for the end of the day just before the report to make
|
||
her move. Before the closing bell, the stock was at $50. Susie sold 20 one-
|
||
month 50-strike calls at 2.10 (a 35 volatility) and bought 1,100 shares of the
|
||
underlying stock at $50 to become delta neutral.
|
||
Exhibit 12.4 shows Susie’s position.
|
||
EXHIBIT 12.4 Delta-neutral short ATM call, long stock position.
|
||
Her delta was just about flat. The delta for the 50 calls was 0.54 per
|
||
contract. Selling a 20-lot creates 10.80 short deltas for her overall position.
|
||
After buying 1,100 shares, she was left long 0.20 deltas, about the
|
||
equivalence of being long 20 shares. Where did her risk lie? Her biggest
|
||
concern was negative gamma. Without even seeing a chart of the stock’s
|
||
price, we can see from the volatility chart that this stock can have big
|
||
moves on earnings. In October, earnings caused a more than 10-point jump
|
||
in realized volatility, to its highest level during the year shown. Whether the
|
||
stock rose or fell is irrelevant. Either event means risk for a premium seller.
|
||
The positive theta looks good on the surface, but in fact, theta provided
|
||
Susie with no significant benefit. Her plan was “in and out and nobody gets
|
||
hurt.” She got into the trade right before the earnings announcement and out
|
||
as soon as implied volatility dropped off. Ideally, she’d like to hold these
|
||
types of trades for less than a day. The true prize is vega.
|
||
Susie was looking for about a 10-point drop in IV, which this option class
|
||
had following the October and January earnings reports. April had a big
|
||
drop in IV, as well, of about eight or nine points. Ultimately, what Susie is
|
||
looking for is reversion to the mean.
|
||
She gauges the normal level of volatility by observing where it is before
|
||
and after the surges caused by earnings. From early November to mid- to
|
||
late- December, the stock’s IV bounced around the 25 percent level. In the
|
||
month of February, the IV was around 25. After the drop-off following
|
||
April earnings and through much of May, the IV was closer to 20 percent.
|
||
In June, IV was just above 25. Susie surmised from this chart that when no
|
||
earnings event is pending, this stock’s options typically trade at about a 25
|
||
percent IV. Therefore, anticipating a 10-point decline from 35 was
|
||
reasonable, given the information available. If Susie gets it right, she stands
|
||
to make $1,150 from vega (10 points × 1.15 vegas × 100).
|
||
As we can see from the right side of the volatility chart in Exhibit 12.3 ,
|
||
Susie did get it right. IV collapsed the next morning by just more than ten
|
||
points. But she didn’t make $1,150; she made less. Why? Realized volatility
|
||
(gamma). The jump in realized volatility shown on the graph is a function
|
||
of the fact that the stock rallied $2 the day after earnings. Negative gamma
|
||
contributed to negative deltas in the face of a rallying market. This negative
|
||
delta affected some of Susie’s potential vega profits.
|
||
So what was Susie’s profit? On this trade she made $800. The next
|
||
morning at the open, she bought back the 50-strike calls at 2.80 (25 IV) and
|
||
sold the stock at $52. To compute her actual profit, she compared the prices
|
||
of the spread when entering the trade with the prices of the spread when
|
||
exiting. Exhibit 12.5 shows the breakdown of the trade.
|
||
EXHIBIT 12.5 Profit breakdown of delta-neutral trade.
|
||
After closing the trade, Susie knew for sure what she made or lost. But
|
||
there are many times when a trader will hold a delta-neutral position for an
|
||
extended period of time. If Susie hadn’t closed her trade, she would have
|
||
looked at her marks to see her P&(L) at that point in time. Marks are the
|
||
prices at which the securities are trading in the actual market, either in real
|
||
time or at end of day. With most online brokers’ trading platforms or
|
||
options-trading software, real-time prices are updated dynamically and
|
||
always at their fingertips. The profit or loss is, then, calculated
|
||
automatically by comparing the actual prices of the opening transaction
|
||
with the current marks.
|
||
What Susie will want to know is why she made $800. Why not more?
|
||
Why not less, for that matter? When trading delta neutral, especially with
|
||
more complex trades involving multiple legs, a manual computation of each
|
||
leg of the spread can be tedious. And to be sure, just looking at the profit or
|
||
loss on each leg doesn’t provide an explanation.
|
||
Susie can see where her profits or losses came from by considering the
|
||
profit or loss for each influence contributing to the option’s value. Exhibit
|
||
12.6 shows the breakdown.
|
||
EXHIBIT 12.6 Profit breakdown by greek.
|
||
Delta
|
||
Susie started out long 0.20 deltas. A $2 rise in the stock price yielded a $40
|
||
profit attributable to that initial delta.
|
||
Gamma
|
||
As the stock rose, the negative delta of the position increased as a result of
|
||
negative gamma. The delta of the stock remained the same, but the negative
|
||
delta of the 50 call grew by the amount of the gamma. Deriving an exact
|
||
P&(L) attributable to gamma is difficult because gamma is a dynamic
|
||
metric: as the stock price changes, so can the gamma. This calculation
|
||
assumes that gamma remains constant. Therefore, the gamma calculation
|
||
here provides only an estimate.
|
||
The initial position gamma of −1.6 means the delta decreases by 3.2 with
|
||
a $2 rise in the stock (–1.60 times the $2 rise in the stock price). Susie, then,
|
||
would multiply −3.2 by $2 to find the loss on −3.2 deltas over a $2 rise. But
|
||
she wasn’t short 3.2 deltas for the whole $2. She started out with zero deltas
|
||
attributable to gamma and ended up being 3.2 shorter from gamma over that
|
||
$2 move. Therefore, if she assumes her negative delta from gamma grew
|
||
steadily from 0 to −3.2, she can estimate her average delta loss over that
|
||
move by dividing by 2.
|
||
Theta
|
||
Susie held this trade one day. Her total theta contributed 0.75 or $75 to her
|
||
position.
|
||
Vega
|
||
Vega is where Susie made her money on this trade. She was able to buy her
|
||
call back 10 IV points lower. The initial position vega was −1.15.
|
||
Multiplying −1.15 by the negative 10-point crush of volatility yields a vega
|
||
profit of $1,150.
|
||
Conclusions
|
||
Studying her position’s P&(L) by observing what happened in her greeks
|
||
provides Susie with an alternate—and in some ways, better—method to
|
||
evaluate her trade. The focus of this delta-neutral trade is less on the price at
|
||
which Susie can buy the calls back to close the position than on the
|
||
volatility level at which she can buy them back, weighed against the P&(L)
|
||
from her other risks. Analyzing her position this way gives her much more
|
||
information than just comparing opening and closing prices. Not only does
|
||
she get a good estimate of how much she made or lost, but she can
|
||
understand why as well.
|
||
The Imprecision of Estimation
|
||
It is important to notice that the P&(L) found by adding up the P&(L)’s
|
||
from the greeks is slightly different from the actual P&(L). There are a
|
||
couple of reasons for this. First, the change in delta resulting from gamma is
|
||
only an estimate, because gamma changes as the stock price changes. For
|
||
small moves in the underlying, the gamma change is less significant, but for
|
||
larger moves, the rate of change of the gamma can be bigger, and it can be
|
||
nonlinear. For example, as an option moves from being at-the-money
|
||
(ATM) to being out-of-the-money (OTM), its gamma decreases. But as the
|
||
option becomes more OTM, its gamma decreases at a slower rate.
|
||
Another reason that the P&(L) from the greeks is different from the actual
|
||
P&(L) is that the greeks are derived from the option-pricing model and are
|
||
therefore theoretical values and do not include slippage.
|
||
Furthermore, the volatility input in this example is rounded a bit for
|
||
simplicity. For example, a volatility of 25 actually yielded a theoretical
|
||
value of 2.796, while the call was bought at 2.80. Because some options
|
||
trade at minimum price increments of a nickel, and none trade in fractions
|
||
of a penny, IV is often rounded.
|
||
Caveat Venditor
|
||
Reversion to the mean holds the promise of profit in this trade, but Susie
|
||
also knows that this strategy does not come without risks of loss. The mean
|
||
to which volatility is expected to revert is not a constant. This benchmark
|
||
can and does change. In this example, if the company had an unexpectedly
|
||
terrible quarter, the stock could plunge sharply. In some cases, this would
|
||
cause IV to find a new, higher level at which to reside. If that had happened
|
||
here, the trade could have been a big loser. Gamma and vega could both
|
||
have wreaked havoc. In trading, there is no sure thing, no matter what the
|
||
chart looks like. Remember, every ship on the bottom of the ocean has a
|
||
chart!
|
||
Volatility Buying
|
||
This same earnings event could have been played entirely differently. A
|
||
different trader, Bobby Buyer, studied the same volatility chart as Susie. It
|
||
is shown again here as Exhibit 12.7 . Bobby also thought there would be a
|
||
rush and crush of IV, but he decided to take a different approach.
|
||
EXHIBIT 12.7 Chip stock volatility before and after earnings reports.
|
||
Source : Chart courtesy of iVolatility.com
|
||
About an hour before the close of business on July 21, just three days
|
||
before earnings announcements, Bobby saw that he could buy volatility at
|
||
30 percent. In Bobby’s opinion, volatility seemed cheap with earnings so
|
||
close. He believed that IV could rise at least five points over the next three
|
||
days. Note that we have the benefit of 20/20 hindsight in the example.
|
||
Near the end of the trading day, the stock was at $49.70. Bobby bought 20
|
||
33-day 50-strike calls at 1.75 (30 volatility) and sold short 1,000 shares of
|
||
the underlying stock at $49.70 to become delta neutral. Exhibit 12.8 shows
|
||
Bobby’s position.
|
||
EXHIBIT 12.8 Delta-neutral long call, short stock position.
|
||
With the stock at $49.70, the calls had +0.51 delta per contract, or +10.2
|
||
for the 20-lot. The short sale of 1,000 shares got Bobby as close to delta-
|
||
neutral as possible without trading an odd lot in the stock. The net position
|
||
delta was +0.20, or about the equivalent of being long 20 shares of stock.
|
||
Bobby’s objective in this case is to profit from an increase in implied
|
||
volatility leading up to earnings.
|
||
While Susie was looking for reversion to the mean, Bobby hoped for a
|
||
further divergence. For Bobby, positive gamma looked like a good thing on
|
||
the surface. However, his plan was to close the position just before earnings
|
||
were released—before the vol crush and before the potential stock-price
|
||
move. With realized volatility already starting to drop off at the time the
|
||
trade was put on, gamma offered little promise of gain.
|
||
As fate would have it, IV did indeed increase. At the end of the day before
|
||
the July earnings report, IV was trading at 35 percent. Bobby closed his
|
||
trade by selling his 20-lot of the 50 calls at 2.10 and buying his 1,000 shares
|
||
of stock back at $50. Exhibit 12.9 shows the P&(L) for each leg of the
|
||
spread.
|
||
EXHIBIT 12.9 Profit breakdown.
|
||
|
||
The calls earned Bobby a total of $700, while the stock lost $300. Of
|
||
course, with this type of trade, it is not relevant which leg was a winner and
|
||
which a loser. All that matters is the bottom line. The net P&(L) on the trade
|
||
was a gain of $400. The gain in this case was mostly a product of IV’s
|
||
rising. Exhibit 12.10 shows the P&(L) per greek.
|
||
EXHIBIT 12.10 Profit breakdown by greek.
|
||
Delta
|
||
The position began long 0.20 deltas. The 0.30-point rise earned Bobby a
|
||
0.06 point gain in delta per contract.
|
||
Gamma
|
||
Bobby had an initial gamma of +1.8. We will use 1.8 for estimating the P&
|
||
(L) in this example, assuming gamma remained constant. A 0.30 rise in the
|
||
stock price multiplied by the 1.8 gamma means that with the stock at $50,
|
||
Bobby was long an additional 0.54 deltas. We can estimate that over the
|
||
course of the 0.30 rise in the stock price, Bobby was long an average of
|
||
0.27 (0.54 ÷ 2). His P&(L) due to gamma, therefore, is a gain of about 0.08
|
||
(0.27 × 0.30).
|
||
Theta
|
||
Bobby held this trade for three days. His total theta cost him 1.92 or $192.
|
||
Vega
|
||
The biggest contribution to Bobby’s profit on this trade was made by the
|
||
spike in IV. He bought 30 volatility and sold 35 volatility. His 1.20 position
|
||
vega earned him 6.00, or $600.
|
||
Conclusions
|
||
The $422 profit is not exact, but the greeks provide a good estimate of the
|
||
hows and the whys behind it. Whether they are used for forecasting profits
|
||
or for doing a postmortem evaluation of a trade, consulting the greeks offers
|
||
information unavailable by just looking at the transaction prices.
|
||
By thinking about all these individual pricing components, a trader can
|
||
make better decisions. For example, about two weeks earlier, Bobby could
|
||
have bought an IV level closer to 26 percent. Being conscious of his theta,
|
||
however, he decided to wait. The $64-a-day theta would have cost him
|
||
$896 over 14 days. That’s much more that the $480 he could have made by
|
||
buying volatility four points lower with his 1.20 vega.
|
||
Risks of the Trade
|
||
Like Susie’s trade, Bobby’s play was not without risk. Certainly theta was a
|
||
concern, but in addition to that was the possibility that IV might not have
|
||
played out as he planned. First, IV might not have risen enough to cover
|
||
three days’ worth of theta. It needed to rise, in this case, about 1.6 volatility
|
||
points for the 1.20 vega to cover the 1.92 theta loss. It might even have
|
||
dropped. An earlier-than-expected announcement that the earnings numbers
|
||
were right on target could have spoiled Bobby’s trade. Or the market simply
|
||
might not have reacted as expected; volatility might not have risen at all, or
|
||
might have fallen. Remember, IV is a function of the market. It does not
|
||
always react as one thinks it should.
|
||
CHAPTER 13
|
||
Delta-Neutral Trading
|
||
Trading Realized Volatility
|
||
So far, we’ve discussed many option strategies in which realized volatility
|
||
is an important component of the trade. And while the management of these
|
||
positions has been the focus of much of the discussion, the ultimate gain or
|
||
loss for many of these strategies has been from movement in a single
|
||
direction. For example, with a long call, the higher the stock rallies the
|
||
better.
|
||
But increases or decreases in realized volatility do not necessarily have an
|
||
exclusive relationship with direction. Recall that realized volatility is the
|
||
annualized standard deviation of daily price movements. Take two similarly
|
||
priced stocks that have had a net price change of zero over a one-month
|
||
period. Stock A had small daily price changes during that period, rising
|
||
$0.10 one day and falling $0.10 the next. Stock B went up or down by $5
|
||
each day for a month. In this rather extreme example, Stock B was much
|
||
more volatile than Stock A, regardless of the fact that the net price change
|
||
for the period for both stocks was zero.
|
||
A stock’s volatility—either high or low volatility—can be capitalized on
|
||
by trading options delta neutral. Simply put, traders buy options delta
|
||
neutral when they believe a stock will have more movement and sell
|
||
options delta neutral when they believe a stock will move less.
|
||
Delta-neutral option sellers profit from low volatility through theta. Every
|
||
day that passes in which the loss from delta/gamma movement is less than
|
||
the gain from theta is a winning day. Traders can adjust their deltas by
|
||
hedging. Delta-neutral option buyers exploit volatility opportunities through
|
||
a trading technique called gamma scalping.
|
||
Gamma Scalping
|
||
Intraday trading is seldom entirely in one direction. A stock may close
|
||
higher or lower, even sharply higher or lower, on the day, but during the day
|
||
there is usually not a steady incremental rise or fall in the stock price. A
|
||
typical intraday stock chart has peaks and troughs all day long. Delta-
|
||
neutral traders who have gamma don’t remain delta neutral as the
|
||
underlying price changes, which inevitably it will. Delta-neutral trading is
|
||
kind of a misnomer.
|
||
In fact, it is gamma trading in which delta-neutral traders engage. For
|
||
long-gamma traders, the position delta gets more positive as the underlying
|
||
moves higher and more negative as the underlying moves lower. An upward
|
||
move in the underlying increases positive deltas, resulting in exponentially
|
||
increasing profits. But if the underlying price begins to retrace downward,
|
||
the gain from deltas can be erased as quickly as it was racked up.
|
||
To lock in delta gains, a trader can adjust the position to delta neutral
|
||
again by selling short stock to cover long deltas. If the stock price declines
|
||
after this adjustment, losses are curtailed thanks to the short stock. In fact,
|
||
the delta will become negative as the underlying price falls, leading to
|
||
growing profits. To lock in profits again, the trader buys stock to cover
|
||
short deltas to once again become delta neutral.
|
||
The net effect is a stock scalp. Positive gamma causes the delta-neutral
|
||
trader to sell stock when the price rises and buy when the stock falls. This
|
||
adds up to a true, realized profit. So positive gamma is a money-making
|
||
machine, right? Not so fast. As in any business, the profits must be great
|
||
enough to cover expenses. Theta is the daily cost of running this gamma-
|
||
scalping business.
|
||
For example, a trader, Harry, notices that the intraday price swings in a
|
||
particular stock have been increasing. He takes a bullish position in realized
|
||
volatility by buying 20 off the 40-strike calls, which have a 50 delta, and
|
||
selling stock on a delta-neutral ratio.
|
||
Buy 20 40-strike calls (50 delta) (long 1,000 deltas)
|
||
Short 1,000 shares at $40 (short 1,000 deltas)
|
||
The immediate delta of this trade is flat, but as the stock moves up or
|
||
down, that will change, presenting gamma-scalping opportunities. Gamma
|
||
scalping is the objective here. The position greeks in Exhibit 13.1 show the
|
||
relationship of the two forces involved in this trade: gamma and theta.
|
||
EXHIBIT 13.1 Greeks for 20-lot delta-neutral long call.
|
||
The relationship of gamma to theta in this sort of trade is paramount to its
|
||
success. Gamma-scalping plays are not buy-and-hold strategies. This is
|
||
active trading. These spreads need to be monitored intraday to take
|
||
advantage of small moves in the underlying security. Harry will sell stock
|
||
when the underlying rises and buy it when the underlying falls, taking a
|
||
profit with each stock trade. The goal for each day that passes is to profit
|
||
enough from positive gamma to cover the day’s theta. But that’s not always
|
||
as easy as it sounds. Let’s study what happens the first seven days after this
|
||
hypothetical trade is executed. For the purposes of this example, we assume
|
||
that gamma remains constant and that the trader is content trading odd lots
|
||
of stock.
|
||
Day One
|
||
The first day proves to be fairly volatile. The stock rallies from $40 to $42
|
||
early in the day. This creates a positive position delta of 5.60, or the
|
||
equivalent of being long about 560 shares. At $42, Harry covers the
|
||
position delta by selling 560 shares of the underlying stock to become delta
|
||
neutral again.
|
||
Later in the day, the market reverses, and the stock drops back down to
|
||
$40 a share. At this point, the position is short 5.60 deltas. Harry again
|
||
adjusts the position, buying 560 shares to get flat. The stock then closes
|
||
right at $40.
|
||
The net result of these two stock transactions is a gain of $1,070. How?
|
||
The gamma scalp minus the theta, as shown below.
|
||
The volatility of day one led to it being a profitable day. Harry scalped 560
|
||
shares for a $2 profit, resulting from volatility in the stock. If the stock
|
||
hadn’t moved as much, the delta would have been smaller, and the dollar
|
||
amount scalped would have been smaller, leading to an exponentially
|
||
smaller profit. If there had been more volatility, profits would have been
|
||
exponentially larger. It would have led to a bigger bite being taken out of
|
||
the market.
|
||
Day Two
|
||
The next day, the market is a bit quieter. There is a $0.40 drop in the price
|
||
of the stock, at which point the position delta is short 1.12. Harry buys 112
|
||
shares at $39.60 to get delta neutral.
|
||
Following Harry’s purchase, the stock slowly drifts back up and is trading
|
||
at $40 near the close. Harry decides to cover his deltas and sell 112 shares
|
||
at $40. It is common to cover all deltas at the end of the day to get back to
|
||
being delta neutral. Remember, the goal of gamma scalping is to trade
|
||
volatility, not direction. Starting the next trading day with a delta, either
|
||
positive or negative, means an often unwanted directional bias and
|
||
unwanted directional risk. Tidying up deltas at the end of the day to get
|
||
neutral is called going home flat.
|
||
Today was not a banner day. Harry did not quite have the opportunity to
|
||
cover the decay.
|
||
|
||
Day Three
|
||
On this day, the market trends. First, the stock rises $0.50, at which point
|
||
Harry sells 140 shares of stock at $40.50 to lock in gains from his delta and
|
||
to get flat. However, the market continues to rally. At $41 a share, Harry is
|
||
long another 1.40 deltas and so sells another 140 shares. The rally
|
||
continues, and at $41.50 he sells another 140 shares to cover the delta.
|
||
Finally, at the end of the day, the stock closes at $42 a share. Harry sells a
|
||
final 140 shares to get flat.
|
||
There was not any literal scalping of stock today. It was all selling.
|
||
Nonetheless, gamma trading led to a profitable day.
|
||
As the stock rose from $40 to $40.50, 140 deltas were created from
|
||
positive gamma. Because the delta was zero at $40 and 140 at $40.50, the
|
||
estimated average delta is found by dividing 140 in half. This estimated
|
||
average delta multiplied by the $0.50 gain on the stock equals a $35 profit.
|
||
The delta was zero after the adjustment made at $40.50, when 140 shares
|
||
were sold. When the stock reached $41, another $35 was reaped from the
|
||
average delta of 70 over the $0.50 move. This process was repeated every
|
||
time the stock rose $0.50 and the delta was covered.
|
||
Day Four
|
||
Day four offers a pleasant surprise for Harry. That morning, the stock opens
|
||
$4 lower. He promptly covers his short delta of 11.2 by buying 1,120 shares
|
||
of the stock at $38 a share. The stock barely moves the rest of the day and
|
||
closes at $38.
|
||
An exponentially larger profit was made because there was $4 worth of
|
||
gains on the growing delta when the stock gapped open. The whole position
|
||
delta was covered $4 lower, so both the delta and the dollar amount gained
|
||
on that delta had a chance to grow. Again, Harry can estimate the average
|
||
delta over the $4 move to be half of 11.20. Multiplying that by the $4 stock
|
||
advance gives him his gamma profit of $2,240. After accounting for theta,
|
||
the net profit is $2,190.
|
||
Days Five and Six
|
||
Days five and six are the weekend; the market is closed.
|
||
|
||
Day Seven
|
||
This is a quiet day after the volatility of the past week. Today, the stock
|
||
slowly drifts up $0.25 by the end of the day. Harry sells 70 shares of stock
|
||
at $38.25 to cover long deltas.
|
||
This day was a loser for Harry, as profits from gamma were not enough to
|
||
cover his theta.
|
||
Art and Science
|
||
Although this was a very simplified example, it was typical of how a
|
||
profitable week of gamma scalping plays out. This stock had a pretty
|
||
volatile week, and overall the week was a winner: there were four losing
|
||
days and three winners. The number of losing days includes the weekends.
|
||
Weekends and holidays are big hurdles for long-gamma traders because of
|
||
the theta loss. The biggest contribution to this being a winning week was
|
||
made by the gap open on day four. Part of the reason was the sheer
|
||
magnitude of the move, and part was the fact that the deltas weren’t covered
|
||
too soon, as they had been on day three.
|
||
In a perfect world, a long-gamma trader will always buy the low of the
|
||
day and sell the high of the day when covering deltas. This, unfortunately,
|
||
seldom happens. Long-gamma traders are very often wrong when trading
|
||
stock to cover deltas.
|
||
Being wrong can be okay on occasion. In fact, it can even be rewarding.
|
||
Day three was profitable despite the fact that 140 shares were sold at
|
||
$40.50, $41, and $41.50. The stock closed at $42; the first three stock trades
|
||
were losers. Harry sold stock at a lower price than the close. But the
|
||
position still made money because of his positive gamma. To be sure, Harry
|
||
would like to have sold all 560 shares at $42 at the end of the day. The day’s
|
||
profits would have been significantly higher.
|
||
The problem is that no one knows where the stock will move next. On
|
||
day three, if the stock had topped out at $40.50 and Harry did not sell stock
|
||
because he thought it would continue higher, he would have missed an
|
||
opportunity. Gamma scalping is not an exact science. The art is to pick
|
||
spots that capture the biggest moves possible without missing opportunities.
|
||
There are many methods traders have used to decide where to cover
|
||
deltas when gamma scalping: the daily standard deviation, a fixed
|
||
percentage of the stock price, a fixed nominal value, covering at a certain
|
||
time of day, “market feel.” No system appears to be absolutely better than
|
||
another. This is where it gets personal. Finding what works for you, and
|
||
what works for the individual stocks you trade, is the art of this science.
|
||
Gamma, Theta, and Volatility
|
||
Clearly, more volatile stocks are more profitable for gamma scalping, right?
|
||
Well . . . maybe. Recall that the higher the implied volatility, the lower the
|
||
gamma and the higher the theta of at-the-money (ATM) options. In many
|
||
cases, the more volatile a stock, the higher the implied volatility (IV). That
|
||
means that a volatile stock might have to move more for a trader to scalp
|
||
enough stock to cover the higher theta.
|
||
Let’s look at the gamma-theta relationship from another perspective. In
|
||
this example, for 0.50 of theta, Harry could buy 2.80 gamma. This
|
||
relationship is based on an assumed 25 percent implied volatility. If IV were
|
||
50 percent, theta for this 20 lot would be higher, and the gamma would be
|
||
lower. At a volatility of 50, Harry could buy 1.40 gammas for 0.90 of theta.
|
||
The gamma is more expensive from a theta perspective, but if the stock’s
|
||
statistical volatility is significantly higher, it may be worth it.
|
||
Gamma Hedging
|
||
Knowing that the gamma and theta figures of Exhibit 13.1 are derived from
|
||
a 25 percent volatility assumption offers a benchmark with which to gauge
|
||
the potential profitability of gamma trading the options. If the stock’s
|
||
standard deviation is below 25 percent, it will be difficult to make money
|
||
being long gamma. If it is above 25 percent, the play becomes easier to
|
||
trade. There is more scalping opportunity, there are more opportunities for
|
||
big moves, and there are more likely to be gaps in either direction. The 25
|
||
percent volatility input not only determines the option’s theoretical value
|
||
but also helps determine the ratio of gamma to theta.
|
||
A 25 percent or higher realized volatility in this case does not guarantee
|
||
the trade’s success or failure, however. Much of the success of the trade has
|
||
to do with how well the trader scalps stock. Covering deltas too soon leads
|
||
to reduced profitability. Covering too late can lead to missed opportunities.
|
||
Trading stock well is also important to gamma sellers with the opposite
|
||
trade: sell calls and buy stock delta neutral. In this example, a trader will
|
||
sell 20 ATM calls and buy stock on a delta-neutral ratio.
|
||
This is a bearish position in realized volatility. It is the opposite of the
|
||
trade in the last example. Consider again that 25 percent IV is the
|
||
benchmark by which to gauge potential profitability. Here, if the stock’s
|
||
volatility is below 25, the chances of having a profitable trade are increased.
|
||
Above 25 is a bit more challenging.
|
||
In this simplified example, a different trader, Mary, plays the role of
|
||
gamma seller. Over the same seven-day period as before, instead of buying
|
||
calls, Mary sold a 20 lot. Exhibit 13.2 shows the analytics for the trade. For
|
||
the purposes of this example, we assume that gamma remains constant and
|
||
the trader is content trading odd lots of stock.
|
||
EXHIBIT 13.2 Greeks for 20-lot delta-neutral short call.
|
||
|
||
Day One
|
||
This was one of the volatile days. The stock rallied from $40 to $42 early in
|
||
the day and had fallen back down to $40 by the end of the day. Big moves
|
||
like this are hard to trade as a short-gamma trader. As the stock rose to $42,
|
||
the negative delta would have been increasing. That means losses were
|
||
adding up at an increasing rate. The only way to have stopped the
|
||
hemorrhaging of money as the stock continued to rise would have been to
|
||
buy stock. Of course, if Mary buys stock and the stock then declines, she
|
||
has a loser.
|
||
Let’s assume the best-case scenario. When the stock reached $42 and she
|
||
had a −560 delta, Mary correctly felt the market was overbought and would
|
||
retrace. Sometimes, the best trades are the ones you don’t make. On this
|
||
day, Mary traded no stock. When the stock reached $40 a share at the end of
|
||
the day, she was back to being delta neutral. Theta makes her a winner
|
||
today.
|
||
Because of the way Mary handled her trade, the volatility of day one was
|
||
not necessarily an impediment to it being profitable. Again, the assumption
|
||
is that Mary made the right call not to negative scalp the stock. Mary could
|
||
have decided to hedge her negative gamma when the stock reach $42 and
|
||
the position delta was at −$560 by buying stock and then selling it at $40.
|
||
There are a number of techniques for hedging deltas resulting from
|
||
negative gamma. The objective of hedging deltas is to avoid losses from the
|
||
stock trending in one direction and creating increasingly adverse deltas but
|
||
not to overtrade stock and negative scalp.
|
||
Day Two
|
||
Recall that this day had a small dip and then recovered to close again at
|
||
$40. It is more reasonable to assume that on this day there was no negative
|
||
scalping. A $0.40 decline is a more typical move in a stock and nothing to
|
||
be afraid of. The 112 delta created by negative gamma when the stock fell
|
||
wouldn’t be perceived as a major concern by most traders in most
|
||
situations. It is reasonable to assume Mary would take no action. Today,
|
||
again, was a winner thanks to theta.
|
||
|
||
Day Three
|
||
Day three saw the stock price trending. It slowly drifted up $2. There would
|
||
have been some judgment calls throughout this day. Again, delta-neutral
|
||
trades are for active traders. Prepare to watch the market much of the day if
|
||
implementing this kind of strategy.
|
||
When the stock was at $41 a share, Mary decided to guard against further
|
||
advances in stock price and hedged her delta. At that point, the position
|
||
would have had a −2.80 delta. She bought 280 shares at $41.
|
||
As the day progressed, the market proved Mary to be right. The stock rose
|
||
to $42 giving the position a delta of −2.80 again. She covered her deltas at
|
||
the end of the day by buying another 280 shares.
|
||
Covering the negative deltas to get flat at $41 proved to be a smart move
|
||
today. It curtailed an exponentially growing delta and let Mary take a
|
||
smaller loss at $41 and get a fresh start. While the day was a loser, it would
|
||
have been $280 worse if she had not purchased stock at $41 before the run-
|
||
up to $42. This is evidenced by the fact that she made a $280 profit on the
|
||
280 shares of stock bought at $41, since the stock closed at $42.
|
||
Day Four
|
||
Day four offered a rather unpleasant surprise. This was the day that the
|
||
stock gapped open $4 lower. This is the kind of day short-gamma traders
|
||
dread. There is, of course, no right way to react to this situation. The stock
|
||
can recover, heading higher; it can continue lower; or it can have a dead-cat
|
||
bounce, remaining where it is after the fall.
|
||
Staring at a quite contrary delta of 11.20, Mary was forced to take action
|
||
by selling stock. But how much stock was the responsible amount to sell for
|
||
a pure short-gamma trader not interested in trading direction? Selling 1,120
|
||
shares would bring the position back to being delta neutral, but the only
|
||
way the trade would stay delta neutral would be if the stock stayed right
|
||
where it was.
|
||
Hedging is always a difficult call for short-gamma traders. Long-gamma
|
||
traders are taking a profit on deltas with every stock trade that covers their
|
||
deltas. Short-gamma traders are always taking a loss on delta. In this case,
|
||
Mary decided to cover half her deltas by selling 560 shares. The other 560
|
||
deltas represent a loss, too; it’s just not locked in.
|
||
Here, Mary made the conscious decision not to go home flat. On the one
|
||
hand, she was accepting the risk of the stock continuing its decline. On the
|
||
other hand, if she had covered the whole delta, she would have been
|
||
accepting the risk of the stock moving in either direction. Mary felt the
|
||
stock would regain some of its losses. She decided to lead the stock a little,
|
||
going into the weekend with a positive delta bias.
|
||
Days Five and Six
|
||
Days five and six are the weekend.
|
||
|
||
Day Seven
|
||
This was the quiet day of the week, and a welcome respite. On this day, the
|
||
stock rose just $0.25. The rise in price helped a bit. Mary was still long 560
|
||
deltas from Friday. Negative gamma took only a small bite out of her profit.
|
||
The P&(L) can be broken down into the profit attributable to the starting
|
||
delta of the trade, the estimated loss from gamma, and the gain from theta.
|
||
Mary ends these seven days of trading worse off than she started. What
|
||
went wrong? The bottom line is that she sold volatility on an asset that
|
||
proved to be volatile. A $4 drop in price of a $42 dollar stock was a big
|
||
move. This stock certainly moved at more than 25 percent volatility. Day
|
||
four alone made this trade a losing proposition.
|
||
Could Mary have done anything better? Yes. In a perfect world, she
|
||
would not have covered her negative deltas on day 3 by buying 280 shares
|
||
at $41 and another 280 at $42. Had she not, this wouldn’t have been such a
|
||
bad week. With the stock ending at $38.25, she lost $1,050 on the 280
|
||
shares she bought at $42 ($3.75 times 280) and lost $770 on the 280 shares
|
||
bought at $41 ($2.75 times 280). Then again, if the stock had continued
|
||
higher, rising beyond $42, those would have been good buys.
|
||
Mary can’t beat herself up too much for protecting herself in a way that
|
||
made sense at the time. The stock’s $2 rally is more to blame than the fact
|
||
that she hedged her deltas. That’s the risk of selling volatility: the stock may
|
||
prove to be volatile. If the stock had not made such a move, she wouldn’t
|
||
have faced the dilemma of whether or not to hedge.
|
||
Conclusions
|
||
The same stock during the same week was used in both examples. These
|
||
two traders started out with equal and opposite positions. They might as
|
||
well have made the trade with each other. And although in this case the vol
|
||
buyer (Harry) had a pretty good week and the vol seller (Mary) had a not-
|
||
so-good week, it’s important to notice that the dollar value of the vol
|
||
buyer’s profit was not the same as the dollar value of the vol seller’s loss.
|
||
Why? Because each trader hedged his or her position differently. Option
|
||
trading is not a zero-sum game.
|
||
Option-selling delta-neutral strategies work well in low-volatility
|
||
environments. Small moves are acceptable. It’s the big moves that can blow
|
||
you out of the water.
|
||
Like long-gamma traders, short-gamma traders have many techniques for
|
||
covering deltas when the stock moves. It is common to cover partial deltas,
|
||
as Mary did on day four of the last example. Conversely, if a stock is
|
||
expected to continue along its trajectory up or down, traders will sometimes
|
||
overhedge by buying more deltas (stock) than they are short or selling more
|
||
than they are long, in anticipation of continued price rises. Daily standard
|
||
deviation derived from implied volatility is a common measure used by
|
||
short-gamma players to calculate price points at which to enter hedges.
|
||
Market feel and other indicators are also used by experienced traders when
|
||
deciding when and how to hedge. Each trader must find what works best for
|
||
him or her.
|
||
Smileys and Frowns
|
||
The trade examples in this chapter have all involved just two components:
|
||
calls and stock. We will explore delta-neutral strategies in other chapters
|
||
that involve more moving parts. Regardless of the specific makeup of the
|
||
position, the P&(L) of each individual leg is not of concern. It is the
|
||
profitability of the position as a whole that matters. For example, after a
|
||
volatile move in a stock occurs, a positive-gamma trader like Harry doesn’t
|
||
care whether the calls or the stock made the profit on the move. The trader
|
||
would monitor the net delta that was produced—positive or negative—and
|
||
cover accordingly. The process is the same for a negative-gamma trader. In
|
||
either case, it is gamma and delta that need to be monitored closely.
|
||
Gamma can make or break a trade. P&(L) diagrams are helpful tools that
|
||
offer a visual representation of the effect of gamma on a position. Many
|
||
option-trading software applications offer P&(L) graphing applications to
|
||
study the payoff of a position with the days to expiration as an adjustable
|
||
variable to study the same trade over time.
|
||
P&(L) diagrams for these delta-neutral positions before the options’
|
||
expiration generally take one of two shapes: a smiley or a frown. The shape
|
||
of the graph depends on whether the position gamma is positive or negative.
|
||
Exhibit 13.3 shows a typical positive-gamma trade.
|
||
EXHIBIT 13.3 P&(L) diagram for a positive-gamma delta-neutral
|
||
position/l.
|
||
This diagram is representative of the P&L of a delta-neutral positive-
|
||
gamma trade calculated using the prices at which the trade was executed.
|
||
With this type of trade, it is intuitive that when the stock price rises or falls,
|
||
profits increase because of favorably changing deltas. This is represented by
|
||
the graph’s smiley-face shape. The corners of the graph rise higher as the
|
||
underlying moves away from the center of the graph.
|
||
The graph is a two-dimensional snapshot showing that the higher or lower
|
||
the underlying moves, the greater the profit. But there are other dimensions
|
||
that are not shown here, such as time and IV. Exhibit 13.4 shows the effects
|
||
of time on a typical long-gamma trade.
|
||
EXHIBIT 13.4 The effect of time on P&(L).
|
||
As time passes, the reduction in profit is reflected by the center point of
|
||
the graph dipping farther into negative territory. That is the effect of time
|
||
decay. The long options will have lost value at that future date with the
|
||
stock still at the same price (all other factors held constant). Still, a move in
|
||
either direction can lead to a profitable position. Ultimately, at expiration,
|
||
the payoff takes on a rigid kinked shape.
|
||
In the delta-neutral long call examples used in this chapter the position
|
||
becomes net long stock if the calls are in-the-money at expiration or net
|
||
short stock if they are out-of-the-money and only the short stock remains.
|
||
Volatility, as well, would move the payoff line vertically. As IV increases,
|
||
the options become worth more at each stock price, and as IV falls, they are
|
||
worth less, assuming all other factors are held constant.
|
||
A delta-neutral short-gamma play would have a P&(L) diagram quite the
|
||
opposite of the smiley-faced long-gamma graph. Exhibit 13.5 shows what is
|
||
called the short-gamma frown.
|
||
EXHIBIT 13.5 Short-gamma frown.
|
||
At first glance, this doesn’t look like a very good proposition. The highest
|
||
point on the graph coincides with a profit of zero, and it only gets worse as
|
||
the price of the underlying rises or falls. This is enough to make any trader
|
||
frown. But again, this snapshot does not show time or volatility. Exhibit
|
||
13.6 shows the payout diagram as time passes.
|
||
EXHIBIT 13.6 The effect of time on the short-gamma frown.
|
||
|
||
A decrease in value of the options from time decay causes an increase in
|
||
profitability. This profit potential pinnacles at the center (strike) price at
|
||
expiration. Rising IV will cause a decline in profitability at each stock price
|
||
point. Declining IV will raise the payout on the Y axis as profitability
|
||
increases at each price point.
|
||
Smileys and frowns are a mere graphical representation of the technique
|
||
discussed in this chapter: buying and selling realized volatility. These P&
|
||
(L) diagrams are limited, because they show the payout only of stock-price
|
||
movement. The profitability of direction-indifferent and direction-neutral
|
||
trading is also influenced by time and implied volatility. These actively
|
||
traded strategies are best evaluated on a gamma-theta basis. Long-gamma
|
||
traders strive each day to scalp enough to cover the day’s theta, while short-
|
||
gamma traders hope to keep the loss due to adverse movement in the
|
||
underlying lower than the daily profit from theta.
|
||
The strategies in this chapter are the same ones traded in Chapter 12. The
|
||
only difference is the philosophy. Ultimately, both types of volatility are
|
||
being traded using these and other option strategies. Implied and realized
|
||
volatility go hand in hand.
|
||
CHAPTER 14
|
||
Studying Volatility Charts
|
||
Implied and realized volatility are both important to option traders. But
|
||
equally important is to understand how the two interact. This relationship is
|
||
best studied by means of a volatility chart. Volatility charts are invaluable
|
||
tools for volatility traders (and all option traders for that matter) in many
|
||
ways.
|
||
First, volatility charts show where implied volatility (IV) is now
|
||
compared with where it’s been in the past. This helps a trader gauge
|
||
whether IV is relatively high or relatively low. Vol charts do the same for
|
||
realized volatility. The realized volatility line on the chart answers three
|
||
questions:
|
||
Have the past 30 days been more or less volatile for the stock than
|
||
usual?
|
||
What is a typical range for the stock’s volatility?
|
||
How much volatility did the underlying historically experience in the
|
||
past around specific recurring events?
|
||
When IV lines and realized volatility lines are plotted on the same chart,
|
||
the divergences and convergences of the two spell out the whole volatility
|
||
story for those who know how to read it.
|
||
Nine Volatility Chart Patterns
|
||
Each individual stock and the options listed on it have their own unique
|
||
realized and implied volatility characteristics. If we studied the vol charts of
|
||
1,000 stocks, we’d likely see around 1,000 different volatility patterns. The
|
||
number of permutations of the relationship of realized to implied volatility
|
||
is nearly infinite, but for the sake of discussion, we will categorize volatility
|
||
charts into nine general patterns. 1
|
||
1. Realized Volatility Rises, Implied
|
||
Volatility Rises
|
||
The first volatility chart pattern is that in which both IV and realized
|
||
volatility rise. In general, this kind of volatility chart can line up three ways:
|
||
implied can rise more than realized volatility; realized can rise more than
|
||
implied; or they can both rise by about the same amount. The chart below
|
||
shows implied volatility rising at a faster rate than realized vol. The general
|
||
theme in this case is that the stock’s price movement has been getting more
|
||
volatile, and the option prices imply even higher volatility in the future.
|
||
This specific type of volatility chart pattern is commonly seen in active
|
||
stocks with a lot of news. Stocks du jour, like some Internet stocks during
|
||
the tech bubble of the late 1990s, story stocks like Apple (AAPL) around
|
||
the release of the iPhone in 2007, have rising volatilities, with the IV
|
||
outpacing the realized volatility. Sometimes individual stocks and even
|
||
broad market indexes and exchange-traded funds (ETFs) see this pattern,
|
||
when the market is declining rapidly, like in the summer of 2011.
|
||
A delta-neutral long-volatility position bought at the beginning of May,
|
||
according to Exhibit 14.1 , would likely have produced a winner. IV took
|
||
off, and there were sure to be plenty of opportunities to profit from gamma
|
||
with realized volatility gaining strength through June and July.
|
||
EXHIBIT 14.1 Realized volatility rises, implied volatility rises.
|
||
Source : Chart courtesy of iVolatility.com
|
||
Looking at the right side of the chart, in late July, with IV at around 50
|
||
percent and realized vol at around 35 percent, and without the benefit of
|
||
knowing what the future will bring, it’s harder to make a call on how to
|
||
trade the volatility. The IV signals that the market is pricing a higher future
|
||
level of stock volatility into the options. If the market is right, gamma will
|
||
be good to have. But is the price right? If realized volatility does indeed
|
||
catch up to implied volatility—that is, if the lines converge at 50 or realized
|
||
volatility rises above IV—a trader will have a good shot at covering theta.
|
||
If it doesn’t, gamma will be very expensive in terms of theta, meaning it
|
||
will be hard to cover the daily theta by scalping gamma intraday.
|
||
The question is: why is IV so much higher than realized? If important
|
||
news is expected to be released in the near future, it may be perfectly
|
||
reasonable for the IV to be higher, even significantly higher, than the
|
||
stock’s realized volatility. One big move in the stock can produce a nice
|
||
profit, as long as theta doesn’t have time to work its mischief. But if there is
|
||
no news in the pipeline, there may be some irrational exuberance—in the
|
||
words of ex-Fed chairman Alan Greenspan—of option buyers rushing to
|
||
acquire gamma that is overvalued in terms of theta.
|
||
In fact, a lack of expectation of news could indicate a potential bearish
|
||
volatility play: sell volatility with the intent of profiting from daily theta
|
||
and a decline in IV. This type of play, however, is not for the fainthearted.
|
||
No one can predict the future. But one thing you can be sure of with this
|
||
trade: you’re in for a wild ride. The lines on this chart scream volatility.
|
||
This means that negative-gamma traders had better be good and had better
|
||
be right!
|
||
In this situation, hedgers and speculators in the market are buying option
|
||
volatility of 50 percent, while the stock is moving at 35 percent volatility.
|
||
Traders putting on a delta-neutral volatility-selling strategy are taking the
|
||
stance that this stock will not continue increasing in volatility as indicated
|
||
by option prices; specifically, it will move at less than 50 percent volatility
|
||
—hopefully a lot less. They are taking the stance that the market’s
|
||
expectations are wrong.
|
||
Instead of realized and implied volatility both trending higher, sometimes
|
||
there is a sharp jump in one or the other. When this happens, it could be an
|
||
indication of a specific event that has occurred (realized volatility) or news
|
||
suddenly released of an expected event yet to come (implied volatility). A
|
||
sharp temporary increase in IV is called a spike, because of its pointy shape
|
||
on the chart. A one-day surge in realized volatility, on the other hand, is not
|
||
so much a volatility spike as it is a realized volatility mesa. Realized
|
||
volatility mesas are shown in Exhibit 14.2 .
|
||
EXHIBIT 14.2 Volatility mesas.
|
||
Source : Chart courtesy of iVolatility.com
|
||
The patterns formed by the gray line in the circled areas of the chart
|
||
shown below are the result of typical one-day surges in realized volatility.
|
||
Here, the 30-day realized volatility rose by nearly 20 percentage points,
|
||
from about 20 percent to about 40 percent, in one day. It remained around
|
||
the 40 percent level for 30 days and then declined 20 points just as fast as it
|
||
rose.
|
||
Was this entire 30-day period unusually volatile? Not necessarily.
|
||
Realized volatility is calculated by looking at price movements within a
|
||
certain time frame, in this case, thirty business days. That means that a
|
||
really big move on one day will remain in the calculation for the entire
|
||
time. Thirty days after the unusually big move, the calculation for realized
|
||
volatility will no longer contain that one-day price jump. Realized volatility
|
||
can then drop significantly.
|
||
2. Realized Volatility Rises, Implied
|
||
Volatility Remains Constant
|
||
This chart pattern can develop from a few different market conditions. One
|
||
scenario is a one-time unanticipated move in the underlying that is not
|
||
expected to affect future volatility. Once the news is priced into the stock,
|
||
there is no point in hedgers’ buying options for protection or speculators’
|
||
buying options for a leveraged bet. What has happened has happened.
|
||
There are other conditions that can cause this type of pattern to
|
||
materialize. In Exhibit 14.3 , the IV was trading around 25 for several
|
||
months, while the realized volatility was lagging. With hindsight, it makes
|
||
perfect sense that something had to give—either IV needed to fall to meet
|
||
realized, or realized would rise to meet market expectations. Here, indeed,
|
||
the latter materialized as realized volatility had a steady rise to and through
|
||
the 25 level in May. Implied, however remained constant.
|
||
EXHIBIT 14.3 Realized volatility rises, implied volatility remains
|
||
constant.
|
||
Source : Chart courtesy of iVolatility.com
|
||
Traders who were long volatility going into the May realized-vol rise
|
||
probably reaped some gamma benefits. But those who got in “too early,”
|
||
buying in January or February, would have suffered too great of theta losses
|
||
before gaining any significant profits from gamma. Time decay (theta) can
|
||
inflict a slow, painful death on an option buyer. By studying this chart in
|
||
hindsight, it is clear that options were priced too high for a gamma scalper
|
||
to have a fighting chance of covering the daily theta before the rise in May.
|
||
This wasn’t necessarily an easy vol-selling trade before the May realized-
|
||
vol rise, either, depending on the trader’s timing. In early February, realized
|
||
did in fact rise above implied, making the short volatility trade much less
|
||
attractive.
|
||
Traders who sold volatility just before the increase in realized volatility in
|
||
May likely ended up losing on gamma and not enough theta profits to make
|
||
up for it. There was no volatility crush like what is often seen following a
|
||
one-day move leading to sharply higher realized volatility. IV simply
|
||
remained pretty steady throughout the month of May and well into June.
|
||
3. Realized Volatility Rises, Implied
|
||
Volatility Falls
|
||
This chart pattern can manifest itself in different ways. In this scenario, the
|
||
stock is becoming more volatile, and options are becoming cheaper. This
|
||
may seem an unusual occurrence, but as we can see in Exhibit 14.4 ,
|
||
volatility sometimes plays out this way. This chart shows two different
|
||
examples of realized vol rising while IV falls.
|
||
EXHIBIT 14.4 Realized volatility rises, implied volatility falls.
|
||
Source : Chart courtesy of iVolatility.com
|
||
The first example, toward the left-hand side of the chart, shows realized
|
||
volatility trending higher while IV is trending lower. Although
|
||
fundamentals can often provide logical reasons for these volatility changes,
|
||
sometimes they just can’t. Both implied and realized volatility are
|
||
ultimately a function of the market. There is a normal oscillation to both of
|
||
these figures. When there is no reason to be found for a volatility change, it
|
||
might be an opportunity. The potential inefficiency of volatility pricing in
|
||
the options market sometimes creates divergences such as this one that vol
|
||
traders scour the market in search of.
|
||
In this first example, after at least three months of IV’s trading marginally
|
||
higher than realized volatility, the two lines converge and then cross. The
|
||
point at which these lines meet is an indication that IV may be beginning to
|
||
get cheap.
|
||
First, it’s a potentially beneficial opportunity to buy a lower volatility than
|
||
that at which the stock is actually moving. The gamma/theta ratio would be
|
||
favorable to gamma scalpers in this case, because the lower cost of options
|
||
compared with stock fluctuations could lead to gamma profits. Second, with
|
||
IV at 35 at the first crossover on this chart, IV is dipping down into the
|
||
lower part of its four-month range. One can make the case that it is getting
|
||
cheaper from a historical IV standpoint. There is arguably an edge from the
|
||
perspective of IV to realized volatility and IV to historical IV. This is an
|
||
example of buying value in the context of volatility.
|
||
Furthermore, if the actual stock volatility is rising, it’s reasonable to
|
||
believe that IV may rise, too. In hindsight we see that this did indeed occur
|
||
in Exhibit 14.4 , despite the fact that realized volatility declined.
|
||
The example circled on the right-hand side of the chart shows IV
|
||
declining sharply while realized volatility rises sharply. This is an example
|
||
of the typical volatility crush as a result of an earnings report. This would
|
||
probably have been a good trade for long volatility traders—even those
|
||
buying at the top. A trader buying options delta neutral the day before
|
||
earnings are announced in this example would likely lose about 10 points of
|
||
vega but would have a good chance to more than make up for that loss on
|
||
positive gamma. Realized volatility nearly doubled, from around 28 percent
|
||
to about 53 percent, in a single day.
|
||
4. Realized Volatility Remains Constant,
|
||
Implied Volatility Rises
|
||
Exhibit 14.5 shows that the stock is moving at about the same volatility
|
||
from the beginning of June to the end of July. But during that time, option
|
||
premiums are rising to higher levels. This is an atypical chart pattern. If this
|
||
was a period leading up to an anticipated event, like earnings, one would
|
||
anticipate realized volatility falling as the market entered a wait-and-see
|
||
mode. But, instead, statistical volatility stays the same. This chart pattern
|
||
may indicate a potential volatility-selling opportunity. If there is no news or
|
||
reason for IV to have risen, it may simply be high tide in the normal ebb
|
||
and flow of volatility.
|
||
EXHIBIT 14.5 Realized volatility remains constant, implied volatility
|
||
rises.
|
||
Source : Chart courtesy of iVolatility.com
|
||
In this example, the historical volatility oscillates between 20 and 24 for
|
||
nearly two months (the beginning of June through the end of July) as IV
|
||
rises from 24 to over 30. The stock price is less volatile than option prices
|
||
indicate. If there is no news to be dug up on the stock to lead one to believe
|
||
there is a valid reason for the IV’s trading at such a level, this could be an
|
||
opportunity to sell IV 5 to 10 points higher than the stock volatility. The
|
||
goal here is to profit from theta or falling vega or both while not losing
|
||
much on negative gamma. As time passes, if the stock continues to move at
|
||
20 to 23 vol, one would expect IV to fall and converge with realized
|
||
volatility.
|
||
5. Realized Volatility Remains Constant,
|
||
Implied Volatility Remains Constant
|
||
This volatility chart pattern shown in Exhibit 14.6 is typical of a boring,
|
||
run-of-the-mill stock with nothing happening in the news. But in this case,
|
||
no news might be good news.
|
||
EXHIBIT 14.6 Realized volatility remains constant, implied volatility
|
||
remains constant.
|
||
Source : Chart courtesy of iVolatility.com
|
||
Again, the gray is realized volatility and the black line is IV.
|
||
It’s common for IV to trade slightly above or below realized volatility for
|
||
extended periods of time in certain assets. In this example, the IV has traded
|
||
in the high teens from late January to late July. During that same time,
|
||
realized volatility has been in the low teens.
|
||
This is a prime environment for option sellers. From a gamma/theta
|
||
standpoint, the odds favor short-volatility traders. The gamma/theta ratio
|
||
provides an edge, setting the stage for theta profits to outweigh negative-
|
||
gamma scalping. Selling calls and buying stock delta neutral would be a
|
||
trade to look at in this situation. But even more basic strategies, such as
|
||
time spreads and iron condors, are appropriate to consider.
|
||
This vol-chart pattern, however, is no guarantee of success. When the
|
||
stock oscillates, delta-neutral traders can negative scalp stock if they are not
|
||
careful by buying high to cover short deltas and then selling low to cover
|
||
long deltas. Time-spread and iron condor trades can fail if volatility
|
||
increases and the increase results from the stock trending in one direction.
|
||
The advantage of buying IV lower than realized, or selling it above, is
|
||
statistical in nature. Traders should use a chart of the stock price in
|
||
conjunction with the volatility chart to get a more complete picture of the
|
||
stock’s price action. This also helps traders make more informed decisions
|
||
about when to hedge.
|
||
6. Realized Volatility Remains Constant,
|
||
Implied Volatility Falls
|
||
Exhibit 14.7 shows two classic implied-realized convergences. From mid-
|
||
September to early November, realized volatility stayed between 22 and 25.
|
||
In mid-October the implied was around 33. Within the span of a few days,
|
||
the implied vol collapsed to converge with the realized at about 22.
|
||
EXHIBIT 14.7 Realized volatility remains constant, implied volatility falls.
|
||
Source : Chart courtesy of iVolatility.com
|
||
There can be many catalysts for such a drop in IV, but there is truly only
|
||
one reason: arbitrage. Although it is common for a small difference between
|
||
implied and realized volatility—1 to 3 points—to exist even for extended
|
||
periods, bigger disparities, like the 7- to 10-point difference here cannot
|
||
exist for that long without good reason.
|
||
If, for example, IV always trades significantly above the realized
|
||
volatility of a particular underlying, all rational market participants will sell
|
||
options because they have a gamma/theta edge. This, in turn, forces options
|
||
prices lower until volatility prices come into line and the arbitrage
|
||
opportunity no longer exists.
|
||
In Exhibit 14.7 , from mid-March to mid-May a similar convergence took
|
||
place but over a longer period of time. These situations are often the result
|
||
of a slow capitulation of market makers who are long volatility. The traders
|
||
give up on the idea that they will be able to scalp enough gamma to cover
|
||
theta and consequently lower their offers to advertise their lower prices.
|
||
7. Realized Volatility Falls, Implied
|
||
Volatility Rises
|
||
This setup shown in Exhibit 14.8 should now be etched into the souls of
|
||
anyone who has been reading up to this point. It is, of course, the picture of
|
||
the classic IV rush that is often seen in stocks around earnings time. The
|
||
more uncertain the earnings, the more pronounced this divergence can be.
|
||
EXHIBIT 14.8 Realized volatility falls, implied volatility rises.
|
||
Source : Chart courtesy of iVolatility.com
|
||
Another classic vol divergence in which IV rises and realized vol falls
|
||
occurs in a drug or biotech company when a Food and Drug Administration
|
||
(FDA) decision on one of the company’s new drugs is imminent. This is
|
||
especially true of smaller firms without big portfolios of drugs. These
|
||
divergences can produce a huge implied–realized disparity of, in some
|
||
cases, literally hundreds of volatility points leading up to the
|
||
announcement.
|
||
Although rising IV accompanied by falling realized volatility can be one
|
||
of the most predictable patterns in trading, it is ironically one of the most
|
||
difficult to trade. When the anticipated news breaks, the stock can and often
|
||
will make a big directional move, and in that case, IV can and likely will
|
||
get crushed. Vega and gamma work against each other in these situations, as
|
||
IV and realized volatility converge. Vol traders will likely gain on one vol
|
||
and lose on the other, but it’s very difficult to predict which will have a
|
||
more profound effect. Many traders simply avoid trading earnings events
|
||
altogether in favor of less erratic opportunities. For most traders, there are
|
||
easier ways to make money.
|
||
8. Realized Volatility Falls, Implied
|
||
Volatility Remains Constant
|
||
This volatility shift can be marked by a volatility convergence, divergence,
|
||
or crossover. Exhibit 14.9 shows the realized volatility falling from around
|
||
30 percent to about 23 percent while IV hovers around 25. The crossover
|
||
here occurs around the middle of February.
|
||
EXHIBIT 14.9 Realized volatility falls, implied volatility remains constant.
|
||
Source : Chart courtesy of iVolatility.com
|
||
The relative size of this volatility change makes the interpretation of the
|
||
chart difficult. The last half of September saw around a 15 percent decline
|
||
in realized volatility. The middle of October saw a one-day jump in realized
|
||
of about 15 points. Historical volatility has had several dynamic moves that
|
||
were larger and more abrupt than the seven-point decline over this six-week
|
||
period. This smaller move in realized volatility is not necessarily an
|
||
indication of a volatility event. It could reflect some complacency in the
|
||
market. It could indicate a slow period with less trading, or it could simply
|
||
be a natural contraction in the ebb and flow of volatility causing the
|
||
calculation of recent stock-price fluctuations to wane.
|
||
What is important in this interpretation is how the options market is
|
||
reacting to the change in the volatility of the stock—where the rubber hits
|
||
the road. The market’s apparent assessment of future volatility is unchanged
|
||
during this period. When IV rises or falls, vol traders must look to the
|
||
underlying stock for a reason. The options market reacts to stock volatility,
|
||
not the other way around.
|
||
Finding fundamental or technical reasons for surges in volatility is easier
|
||
than finding specific reasons for a decline in volatility. When volatility falls,
|
||
it is usually the result of a lack of news, leading to less price action. In this
|
||
example, probably nothing happened in the market. Consequently, the stock
|
||
volatility drifted lower. But it fell below the lowest IV level seen for the six-
|
||
month period leading up to the crossover. It was probably hard to take a
|
||
confident stance in volatility immediately following the crossover. It is
|
||
difficult to justify selling volatility when the implied is so cheap compared
|
||
with its historic levels. And it can be hard to justify buying volatility when
|
||
the options are priced above the stock volatility.
|
||
The two-week period before the realized line moved beneath the implied
|
||
line deserves closer study. With the IV four or five points lower than the
|
||
realized volatility in late January, traders may have been tempted to buy
|
||
volatility. In hindsight, this trade might have been profitable, but there was
|
||
surely no guarantee of this. Success would have been greatly contingent on
|
||
how the traders managed their deltas, and how well they adapted as realized
|
||
volatility fell.
|
||
During the first half of this period, the stock volatility remained above
|
||
implied. For an experienced delta-neutral trader, scalping gamma was likely
|
||
easy money. With the oscillations in stock price, the biggest gamma-
|
||
scalping risk would have been to cover too soon and miss out on
|
||
opportunities to take bigger profits.
|
||
Using the one-day standard deviation based on IV (described in Chapter
|
||
3) might have produced early covering for long-gamma traders. Why?
|
||
Because in late January, the standard deviation derived from IV was lower
|
||
than the actual standard deviation of the stock being traded. In the latter half
|
||
of the period being studied, the end of February on this chart, using the one-
|
||
day standard deviation based on IV would have produced scalping that was
|
||
too late. This would have led to many missed opportunities.
|
||
Traders entering hedges at regular nominal intervals—every $0.50, for
|
||
example—would probably have needed to decrease the interval as volatility
|
||
ebbed. For instance, if in late January they were entering orders every
|
||
$0.50, by late February they might have had to trade every $0.40.
|
||
9. Realized Volatility Falls, Implied
|
||
Volatility Falls
|
||
This final volatility-chart permutation incorporates a fall of both realized
|
||
and IV. The chart in Exhibit 14.10 clearly represents the slow culmination
|
||
of a highly volatile period. This setup often coincides with news of some
|
||
scary event’s being resolved—a law suit settled, unpopular upper
|
||
management leaving, rumors found to be false, a happy ending to political
|
||
issues domestically or abroad, for example. After a sharp sell-off in IV,
|
||
from 75 to 55, in late October, marking the end of a period of great
|
||
uncertainty, the stock volatility began a steady decline, from the low 50s to
|
||
below 25. IV fell as well, although it remained a bit higher for several
|
||
months.
|
||
EXHIBIT 14.10 Realized volatility falls, implied volatility falls.
|
||
Source : Chart courtesy of iVolatility.com
|
||
In some situations where an extended period of extreme volatility appears
|
||
to be coming to an end, there can be some predictability in how IV will
|
||
react. To be sure, no one knows what the future holds, but when volatility
|
||
starts to wane because a specific issue that was causing gyrations in the
|
||
stock price is resolved, it is common, and intuitive, for IV to fall with the
|
||
stock volatility. This is another type of example of reversion to the mean.
|
||
There is a potential problem if the high-volatility period lasted for an
|
||
extended period of time. Sometimes, it’s hard to get a feel for what the
|
||
mean volatility should be. Or sometimes, because of the event, the stock is
|
||
fundamentally different—in the case of a spin-off, merger, or other
|
||
corporate action, for example. When it is difficult or impossible to look
|
||
back at a stock’s performance over the previous 6 to 12 months and
|
||
appraise what the normal volatility should be, one can look to the volatility
|
||
of other stocks in the same industry for some guidance.
|
||
Stocks that are substitutable for one another typically trade at similar
|
||
volatilities. From a realized volatility perspective, this is rather intuitive.
|
||
When one stock within an industry rises or falls, others within the same
|
||
industry tend to follow. They trade similarly and therefore experience
|
||
similar volatility patterns. If the stock volatility among names within one
|
||
industry tends to be similar, it follows that the IV should be, too.
|
||
Regardless which of the nine patterns discussed here show up, or how the
|
||
volatilities line up, there is one overriding observation that’s representative
|
||
of all volatility charts: vol charts are simply graphical representations of
|
||
realized and implied volatility that help traders better understand the two
|
||
volatilities’ interaction. But the divergences and convergences in the
|
||
examples in this chapter have profound meaning to the volatility trader.
|
||
Combined with a comparison of current and past volatility (both realized
|
||
and implied), they give traders insight into how cheap or expensive options
|
||
are.
|
||
Note
|
||
1 . The following examples use charts supplied by iVolatility.com . The
|
||
gray line is the 30-day realized volatility, and the black line is the implied
|
||
volatility.
|
||
PART IV
|
||
Advanced Option Trading
|
||
CHAPTER 15
|
||
Straddles and Strangles
|
||
Straddles and strangles are the quintessential volatility strategies. They are
|
||
the purest ways to buy and sell realized and implied volatility. This chapter
|
||
discusses straddles and strangles, how they work, when to use them, what to
|
||
look out for, and the differences between the two.
|
||
Long Straddle
|
||
Definition : Buying one call and one put in the same option class, in the
|
||
same expiration cycle, and with the same strike price.
|
||
Linearly, the long straddle is the best of both worlds—long a call and a
|
||
put. If the stock rises, the call enjoys the unlimited potential for profit while
|
||
the put’s losses are decidedly limited. If the stock falls, the put’s profit
|
||
potential is bound only by the stock’s falling to zero, while the call’s
|
||
potential loss is finite. Directionally, this can be a win-win situation—as
|
||
long as the stock moves enough for one option’s profit to cover the loss on
|
||
the other. The risk, however, is that this may not happen. Holding two long
|
||
options means a big penalty can be paid for stagnant stocks.
|
||
The Basic Long Straddle
|
||
The long straddle is an option strategy to use when a trader is looking for a
|
||
big move in a stock but is uncertain which direction it will move.
|
||
Technically, the Commodity Channel Index (CCI), Bollinger bands, or
|
||
pennants are some examples of indicators which might signal the possibility
|
||
of a breakout. Or fundamental data might call for a revaluation of the stock
|
||
based on an impending catalyst. In either case, a long straddle, is a way for
|
||
traders to position themselves for the expected move, without regard to
|
||
direction. In this example, we’ll study a hypothetical $70 stock poised for a
|
||
breakout. We’ll buy the one-month 70 straddle for 4.25.
|
||
Exhibit 15.1 shows the payout of the straddle at expiration.
|
||
EXHIBIT 15.1 At-expiration diagram for a long straddle.
|
||
At expiration, with the stock at $70, neither the call nor the put is in-the-
|
||
money. The straddle expires worthless, leaving a loss of 4.25 in its wake
|
||
from erosion. If, however, the stock is above or below $70, either the call or
|
||
the put will have at least some value. The farther the stock price moves
|
||
from the strike price in either direction, the higher the net value of the
|
||
options.
|
||
Above $70, the call has value. If the underlying is at $74.25 at expiration,
|
||
the put will expire worthless, but the call will be worth 4.25—the price
|
||
initially paid for the straddle. Above this break-even price, the trade is a
|
||
winner, and the higher, the better. Below $70, the put has value. If the
|
||
underlying is at $65.75 at expiration, the call expires, and the put is worth
|
||
4.25. Below this breakeven, the straddle is a winner, and the lower, the
|
||
better.
|
||
Why It Works
|
||
In this basic example, if the underlying is beyond either of the break-even
|
||
points at expiration, the trade is a winner. The key to understanding this is
|
||
the fact that at expiration, the loss on one option is limited—it can only fall
|
||
to zero—but the profit potential on the other can be unlimited.
|
||
In practice, most active traders will not hold a straddle until expiration.
|
||
Even if the trade is not held to term, however, movement is still beneficial
|
||
—in fact, it is more beneficial, because time decay will not have depleted
|
||
all the extrinsic value of the options. Movement benefits the long straddle
|
||
because of positive gamma. But movement is a race against the clock—a
|
||
race against theta. Theta is the cost of trading the long straddle. Only pay it
|
||
for as long as necessary. When the stock’s volatility appears poised to ebb,
|
||
exit the trade.
|
||
Exhibit 15.2 shows the P&(L) of the straddle both at expiration and at the
|
||
time the trade was made.
|
||
EXHIBIT 15.2 Long straddle P&(L) at initiation and expiration.
|
||
Because this is a short-term at-the-money (ATM) straddle, we will
|
||
assume for simplicity that it has a delta of zero. 1 When the trade is
|
||
consummated, movement can only help, as indicated by the dotted line on
|
||
the exhibit. This is the classic graphic representation of positive gamma—
|
||
the smiley face. When the stock moves higher, the call gains value at an
|
||
increasing rate while the put loses value at a decreasing rate. When the
|
||
stock moves lower, the put gains at an increasing rate while the call loses at
|
||
a decreasing rate. This is positive gamma.
|
||
This still may not be an entirely fair representation of how profits are
|
||
earned. The underlying is not required to move continuously in one
|
||
direction for traders to reap gamma profits. As described in Chapter 13,
|
||
traders can scalp gamma by buying and selling stock to offset long or short
|
||
deltas created by movement in the underlying. When traders scalp gamma,
|
||
they lock in profits as the stock price oscillates.
|
||
The potential for gamma scalping is an important motivation for straddle
|
||
buyers. Gamma scalping a straddle gives traders the chance to profit from a
|
||
stock that has dynamic price swings. It should be second nature to volatility
|
||
traders to understand that theta is the trade-off of gamma scalping.
|
||
The Big V
|
||
Gamma and theta are not alone in the straddle buyer’s thoughts. Vega is a
|
||
major consideration for a straddle buyer, as well. In a straddle, there are two
|
||
long options of the same strike, which means double the vega risk of a
|
||
single-leg trade at that strike. With no short options in this spread, the
|
||
implied-volatility exposure is concentrated. For example, if the call has a
|
||
vega of 0.05, the put’s vega at that same strike will also be about 0.05. This
|
||
means that buying one straddle gives the trader exposure of around 10 cents
|
||
per implied volatility (IV) point. If IV rises by one point, the trader makes
|
||
$10 per one-lot straddle, $20 for two points, and so on. If IV falls one point,
|
||
the trader loses $10 per straddle, $20 for two points, and so on. Traders who
|
||
want maximum positive exposure to volatility find it in long straddles.
|
||
This strategy is a prime example of the marriage of implied and realized
|
||
volatility. Traders who buy straddles because they are bullish on realized
|
||
volatility will also have bullish positions in implied volatility—like it or
|
||
not. With this in mind, traders must take care to buy gamma via a straddle
|
||
that it is not too expensive in terms of the implied volatility. A winning
|
||
gamma trade can quickly become a loser because of implied volatility.
|
||
Likewise, traders buying straddles to speculate on an increase in implied
|
||
volatility must take the theta risk of the trade very seriously. Time can eat
|
||
away all a trade’s vega profits and more. Realized and implied exposure go
|
||
hand in hand.
|
||
The relationship between gamma and vega depends on, among other
|
||
things, the time to expiration. Traders have some control over the amount of
|
||
gamma relative to the amount of vega by choosing which expiration month
|
||
to trade. The shorter the time until expiration, the higher the gammas and
|
||
the lower the vegas of ATM options. Gamma traders may be better served
|
||
by buying short-term contracts that coincide with the period of perceived
|
||
high stock volatility.
|
||
If the intent of the straddle is to profit from vega, the choice of the month
|
||
to trade depends on which month’s volatility is perceived to be too high or
|
||
too low. If, for example, the front-month IV looks low compared with
|
||
historical IV, current and historical realized volatility, and the expected
|
||
future volatility, but the back months’ IVs are higher and more in line with
|
||
these other metrics, there would be no point in buying the back-month
|
||
options. In this case, traders would need to buy the month that they think is
|
||
cheap.
|
||
Trading the Long Straddle
|
||
Option trading is all about optimizing the statistical chances of success. A
|
||
long-straddle trade makes the most sense if traders think they can make
|
||
money on both implied volatility and gamma. Many traders make the
|
||
mistake of buying a straddle just before earnings are announced because
|
||
they anticipate a big move in the stock. Of course, stock-price action is only
|
||
half the story. The option premium can be extraordinarily expensive just
|
||
before earnings, because the stock move is priced into the options. This is
|
||
buying after the rush and before the crush. Although some traders are
|
||
successful specializing in trading earnings, this is a hard way to make
|
||
money.
|
||
Ideally, the best time to buy volatility is before the move is priced in—
|
||
that is, before everyone else does. This is conceptually the same as buying a
|
||
stock in anticipation of bullish news. Once news comes out, the stock
|
||
rallies, and it is often too late to participate in profits. The goal is to get in at
|
||
the beginning of the trend, not the end—the same goal as in trading
|
||
volatility.
|
||
As in analyzing a stock, fundamental and technical tools exist for
|
||
analyzing volatility—namely, news and volatility charts. For fundamentals,
|
||
buy the rumor, sell the news applies to the rush and crush of implied
|
||
volatility. Previous chapters discussed fundamental events that affect
|
||
volatility; be prepared to act fast when volatility-changing situations present
|
||
themselves. With charts, the elementary concept of buy low, sell high is
|
||
obvious, yet profound. Review Chapter 14 for guidance on reading
|
||
volatility charts.
|
||
With all trading, getting in is easy. It’s managing the position, deciding
|
||
when to hedge and when to get out that is the tricky part. This is especially
|
||
true with the long straddle. Straddles are intended to be actively managed.
|
||
Instead of waiting for a big linear move to evolve over time, traders can
|
||
take profits intermittently through gamma scalping. Furthermore, they hold
|
||
the trade only as long as gamma scalping appears to be a promising
|
||
opportunity.
|
||
Legging Out
|
||
There are many ways to exiting a straddle. In the right circumstances,
|
||
legging out is the preferred method. Instead of buying and selling stock to
|
||
lock in profits and maintain delta neutrality, traders can reduce their
|
||
positions by selling off some of the calls or puts that are part of the straddle.
|
||
In this technique, when the underlying rises, traders sell as many calls as
|
||
needed to reduce the delta to zero. As the underlying falls, they sell enough
|
||
puts to reduce their position to zero delta. As the stock oscillates, they
|
||
whittle away at the position with each hedging transaction. This serves the
|
||
dual purpose of taking profits and reducing risk.
|
||
A trader, Susan, has been studying Acme Brokerage Co. (ABC). Susan
|
||
has noticed that brokerage stocks have been fairly volatile in recent past.
|
||
Exhibit 15.3 shows an analysis of Acme’s volatility over the past 30 days.
|
||
EXHIBIT 15.3 Acme Brokerage Co. volatility.
|
||
Stock Price Realized VolatilityFront-Month Implied Volatility
|
||
30-day high $78.6630-day high 47%30-day high 55%
|
||
30-day low $66.9430-day low 36%30-day low 34%
|
||
Current px $74.80Current vol 36%Current vol 36%
|
||
During this period, Acme stock ranged more than $11 in price. In this
|
||
example, Acme’s volatility is a function of interest rate concerns and other
|
||
macroeconomic issues affecting the brokerage industry as a whole. As the
|
||
stock price begins to level off in the latter half of the 30-day period, realized
|
||
volatility begins to ebb. The front month’s IV recedes toward recent lows as
|
||
well. At this point, both realized and implied volatility converge at 36
|
||
percent. Although volatility is at its low for the past month, it is still
|
||
relatively high for a brokerage stock under normal market conditions.
|
||
Susan does not believe that the volatility plaguing this stock is over. She
|
||
believes that an upcoming scheduled Federal Reserve Board announcement
|
||
will lead to more volatility. She perceives this to be a volatility-buying
|
||
opportunity. Effectively, she wants to buy volatility on the dip. Susan pays
|
||
5.75 for 20 July 75-strike straddles.
|
||
Exhibit 15.4 shows the analytics of this trade with four weeks until
|
||
expiration.
|
||
EXHIBIT 15.4 Analytics for long 20 Acme Brokerage Co. 75-strike
|
||
straddles.
|
||
As with any trade, the risk is that the trader is wrong. The risk here is
|
||
indicated by the −2.07 theta and the +3.35 vega. Susan has to scalp an
|
||
average of at least $207 a day just to break even against the time decay. And
|
||
if IV continues to ebb down to a lower, more historically normal, level, she
|
||
needs to scalp even more to make up for vega losses.
|
||
Effectively, Susan wants both realized and implied volatility to rise. She
|
||
paid 36 volatility for the straddle. She wants to be able to sell the options at
|
||
a higher vol than 36. In the interim, she needs to cover her decay just to
|
||
break even. But in this case, she thinks the stock will be volatile enough to
|
||
cover decay and then some. If Acme moves at a volatility greater than 36,
|
||
her chances of scalping profitably are more favorable than if it moves at
|
||
less than 36 vol. The following is one possible scenario of what might have
|
||
happened over two weeks after the trade was made.
|
||
Week One
|
||
During the first week, the stock’s volatility tapered off a bit more, but
|
||
implied volatility stayed firm. After some oscillation, the realized volatility
|
||
ended the week at 34 percent while IV remained at 36 percent. Susan was
|
||
able to scalp stock reasonably well, although she still didn’t cover her seven
|
||
days of theta. Her stock buys and sells netted a gain of $1,100. By the end
|
||
of week one, the straddle was 5.10 bid. If she had sold the straddle at the
|
||
market, she would have ended up losing $200.
|
||
Susan decided to hold her position. Toward the end of week two, there
|
||
would be the Federal Open Market Committee (FOMC) meeting.
|
||
Week Two
|
||
The beginning of the week saw IV rise as the event drew near. By the close
|
||
on Tuesday, implied volatility for the straddle was 40 percent. But realized
|
||
volatility continued its decline, which meant Susan was not able to scalp to
|
||
cover the theta of Saturday, Sunday, Monday, and Tuesday. But, the straddle
|
||
was now 5.20 bid, 0.10 higher than it had been on previous Friday. The
|
||
rising IV made up for most of the theta loss. At this point, Susan could have
|
||
sold her straddle to scratch her trade. She would have lost $1,100 on the
|
||
straddle [(5.20 − 5.75) × 20] but made $1,100 by scalping gamma in the
|
||
first week. Susan decided to wait and see what the Fed chairman had to say.
|
||
By week’s end, the trade had proved to be profitable. After the FOMC
|
||
meeting, the stock shot up more than $4 and just as quickly fell. It
|
||
continued to bounce around a bit for the rest of the week. Susan was able to
|
||
lock in $5,200 from stock scalps. After much gyration over this two-week
|
||
period, the price of Acme stock incidentally returned to around the same
|
||
price it had been at when Susan bought her straddle: $74.50. As might have
|
||
been expected after the announcement, implied volatility softened. By
|
||
Friday, IV had fallen to 30. Realized volatility was sharply higher as a result
|
||
of the big moves during the week that were factored into the 30-day
|
||
calculation.
|
||
With seven more days of decay and a lower implied volatility, the straddle
|
||
was 3.50 bid at midafternoon on Friday. Susan sold her 20-lot to close the
|
||
position. Her profit for week two was $2,000.
|
||
What went into Susan’s decision to close her position? Susan had two
|
||
objectives: to profit from a rise in implied volatility and to profit from a rise
|
||
in realized volatility. The rise in IV did indeed occur, but not immediately.
|
||
By Tuesday of the second week, vega profits were overshadowed by theta
|
||
losses.
|
||
Gamma was the saving grace with this trade. The bulk of the gain
|
||
occurred in week two when the Fed announcement was made. Once that
|
||
event passed, the prospects for covering theta looked less attractive. They
|
||
were further dimmed by the sharp drop in implied volatility from 40 to 30.
|
||
In this hypothetical scenario, the trade ended up profitable. This is not
|
||
always the case. Here the profit was chiefly produced by one or two high-
|
||
volatility days. Had the stock not been unusually volatile during this time,
|
||
the trade would have been a certain loser. Even though implied volatility
|
||
had risen four points by Tuesday of the second week, the trade did not yield
|
||
a profit. The time decay of holding two options can make long straddles a
|
||
tough strategy to trade.
|
||
Short Straddle
|
||
Definition : Selling one call and one put in the same option class, in the
|
||
same expiration cycle, and with the same strike price.
|
||
Just as buying a straddle is a pure way to buy volatility, selling a straddle
|
||
is a way to short it. When a trader’s forecast calls for lower implied and
|
||
realized volatility, a straddle generates the highest returns of all volatility-
|
||
selling strategies. Of course, with high reward necessarily comes high risk.
|
||
A short straddle is one of the riskiest positions to trade.
|
||
Let’s look at a one-month 70-strike straddle sold at 4.25.
|
||
The risk is easily represented graphically by means of a P&(L) diagram.
|
||
Exhibit 15.5 shows the risk and reward of this short straddle.
|
||
EXHIBIT 15.5 Short straddle P&(L) at initiation and expiration.
|
||
If the straddle is held until expiration and the underlying is trading below
|
||
the strike price, the short put is in-the-money (ITM). The lower the stock,
|
||
the greater the loss on the +1.00 delta from the put. The trade as a whole
|
||
will be a loser if the underlying is below the lower of the two break-even
|
||
points—in this case $65.75. This point is found by subtracting the premium
|
||
received from the strike. Before expiration, negative gamma adversely
|
||
affects profits as the underlying falls. The lower the underlying is trading
|
||
below the strike price, the greater the drain on P&(L) due to the positive
|
||
delta of the short put.
|
||
It is the same proposition if the underlying is above $70 at expiration. But
|
||
in this case, it is the short call that would be in-the-money. The higher the
|
||
underlying price, the more the −1.00 delta adversely impacts P&(L). If at
|
||
expiration the underlying is above the higher breakeven, which in this case
|
||
is $74.25 (the strike plus the premium), the trade is a loser. The higher the
|
||
underlying, the worse off the trade. Before expiration, negative gamma
|
||
creates negative deltas as the underlying climbs above the strike, eating
|
||
away at the potential profit, which is the net premium received.
|
||
The best-case scenario is that the underlying is right at $70 at the closing
|
||
bell on expiration Friday. In this situation, neither option is ITM, meaning
|
||
that the 4.25 premium is all profit. In reaping the maximum profit, both
|
||
time and price play roles. If the position is closed before expiration, implied
|
||
volatility enters into the picture as well.
|
||
It’s important to note that just because neither option is ITM if the
|
||
underlying is right at $70 at expiration, it doesn’t mean with certainty that
|
||
neither option will be assigned. Sometimes options that are ATM or even
|
||
out-of-the-money (OTM) get assigned. This can lead to a pleasant or
|
||
unpleasant surprise the Monday morning following expiration. The risk of
|
||
not knowing whether or not you will be assigned—that is, whether or not
|
||
you have a position in the underlying security—is a risk to be avoided. It is
|
||
the goal of every trader to remove unnecessary risk from the equation.
|
||
Buying the call and the put for 0.05 or 0.10 to close the position is a small
|
||
price to pay when one considers the possibility of waking up Monday
|
||
morning to find a loss of hundreds of dollars per contract because a position
|
||
you didn’t even know you owned had moved against you. Most traders
|
||
avoid this risk, referred to as pin risk, by closing short options before
|
||
expiration.
|
||
The Risks with Short Straddles
|
||
Looking at an at-expiration diagram or even analyzing the gamma/theta
|
||
relationship of a short straddle may sometimes lead to a false sense of
|
||
comfort. Sometimes it looks as if short straddles need a pretty big move to
|
||
lose a lot of money. So why are they definitely among the riskiest strategies
|
||
to trade? That is a matter of perspective.
|
||
Option trading is about risk management. Dealing with a proverbial train
|
||
wreck every once in a while is part of the game. But the big disasters can
|
||
end one’s trading career in an instant. Because of its potential—albeit
|
||
sometimes small potential—for a colossal blowup, the short straddle is,
|
||
indeed, one of the riskiest positions one can trade. That said, it has a place
|
||
in the arsenal of option strategies for speculative traders.
|
||
Trading the Short Straddle
|
||
A short straddle is a trade for highly speculative traders who think a security
|
||
will trade within a defined range and that implied volatility is too high.
|
||
While a long straddle needs to be actively traded, a short straddle needs to
|
||
be actively monitored to guard against negative gamma. As adverse deltas
|
||
get bigger because of stock price movement, traders have to be on alert,
|
||
ready to neutralize directional risk by offsetting the delta with stock or by
|
||
legging out of the options. To be sure, with a short straddle, every stock
|
||
trade locks in a loss with the intent of stemming future losses. The ideal
|
||
situation is that the straddle is held until expiration and expires with the
|
||
underlying right at $70 with no negative-gamma scalping.
|
||
Short-straddle traders must take a longer-term view of their positions than
|
||
long-straddle traders. Often with short straddles, it is ultimately time that
|
||
provides the payout. While long straddle traders would be inclined to watch
|
||
gamma and theta very closely to see how much movement is required to
|
||
cover each day’s erosion, short straddlers are more inclined to focus on the
|
||
at-expiration diagram so as not to lose sight of the end game.
|
||
There are some situations that are exceptions to this long-term focus. For
|
||
example, when implied volatility gets to be extremely high for a particular
|
||
option class relative to both the underlying stock’s volatility and the
|
||
historical implied volatility, one may want to sell a straddle to profit from a
|
||
fall in IV. This can lead to leveraged short-term profits if implied volatility
|
||
does, indeed, decline.
|
||
Because of the fact that there are two short options involved, these
|
||
straddles administer a concentrated dose of negative vega. For those willing
|
||
to bet big on a decline in implied volatility, a short straddle is an eager
|
||
croupier. These trades are delta neutral and double the vega of a single-leg
|
||
trade. But they’re double the gamma, too. As with the long straddle,
|
||
realized and implied volatility levels are both important to watch.
|
||
Short-Straddle Example
|
||
For this example, a trader, John, has been watching Federal XYZ Corp.
|
||
(XYZ) for a year. During the 12 months that John has followed XYZ, its
|
||
front-month implied volatility has typically traded at around 20 percent, and
|
||
its realized volatility has fluctuated between 15 and 20 percent. The past 30
|
||
days, however, have been a bit more volatile. Exhibit 15.6 shows XYZ’s
|
||
recent volatility.
|
||
EXHIBIT 15.6 XYZ volatility.
|
||
Stock Price Realized VolatilityFront-Month Implied Volatility
|
||
30-day high $111.7130-day high 26%30-day high 30%
|
||
30-day low $102.0530-day low 21%30-day low 24%
|
||
Current px $104.75Current vol 22%Current vol 26%
|
||
The stock volatility has begun to ease, trading now at a 22 volatility
|
||
compared with the 30-day high of 26, but still not down to the usual 15-to-
|
||
20 range. The stock, in this scenario, has traded in a channel. It currently
|
||
lies in the lower half of its recent range. Although the current front-month
|
||
implied volatility is in the lower half of its 30-day range, it’s historically
|
||
high compared with the 20 percent level that John has been used to seeing,
|
||
and it’s still four points above the realized volatility. John believes that the
|
||
conditions that led to the recent surge in volatility are no longer present. His
|
||
forecast is for the stock volatility to continue to ease and for implied
|
||
volatility to continue its downtrend as well and revert to its long-term mean
|
||
over the next week or two. John sells 10 September 105 straddles at 5.40.
|
||
Exhibit 15.7 shows the greeks for this trade.
|
||
EXHIBIT 15.7 Greeks for short XYZ straddle.
|
||
|
||
The goal here is for implied volatility to fall to around 20. If it does, John
|
||
makes $1,254 (6 vol points × 2.09 vega). He also thinks theta gains will
|
||
outpace gamma losses. The following is a two-week examination of one
|
||
possible outcome for John’s trade.
|
||
Week One
|
||
The first week in this example was a profitable one, but it came with
|
||
challenges. John paid for his winnings with a few sleepless nights. On the
|
||
Monday following his entry into the trade, the stock rose to $106. While
|
||
John collected a weekend’s worth of time decay, the $1.25 jump in stock
|
||
price ate into some of those profits and naturally made him uneasy about
|
||
the future.
|
||
At this point, John was sitting on a profit, but his position delta began to
|
||
grow negative, to around −1.22 [(–1.18 × 1.25) + 0.26]. For a $104.75
|
||
stock, a move of $1.25—or just over 1 percent—is not out of the ordinary,
|
||
but it put John on his guard. He decided to wait and see what happened
|
||
before hedging.
|
||
The following day, the rally continued. The stock was at $107.30 by
|
||
noon. His delta was around −3. In the face of an increasingly negative delta,
|
||
John weighed his alternatives: He could buy back some of his calls to offset
|
||
his delta, which would have the added benefit of reducing his gamma as
|
||
well. He could buy stock to flatten out. Lastly, he could simply do nothing
|
||
and wait. John felt the stock was overbought and might retrace. He also still
|
||
believed volatility would fall. He decided to be patient and enter a stop
|
||
order to buy all of his deltas at $107.50 in case the stock continued trending
|
||
up. The XYZ shares closed at $107.45 that day.
|
||
This time inaction proved to be the best action. The stock did retrace.
|
||
Week one ended with Federal XYZ back down around $105.50. The IV of
|
||
the straddle was at 23. The straddle finished up week one offered at $4.10.
|
||
Week Two
|
||
The future was looking bright at the start of week two until Wednesday.
|
||
Wednesday morning saw XYZ gap open to $109. When you have a short
|
||
straddle, a $3.50 gap move in the underlying tends to instantly give you a
|
||
sinking feeling in the pit of your stomach. But the damage was truly not that
|
||
bad. The offer in the straddle was 4.75, so the position was still a winner if
|
||
John bought it back at this point.
|
||
Gamma/delta hurt. Theta helped. A characteristic that enters into this
|
||
trade is volatility’s changing as a result of movement in the stock price.
|
||
Despite the fact that the stock gapped $3.50 higher, implied volatility fell by
|
||
1 percent, to 22. This volatility reaction to the underlying’s rise in price is
|
||
very common in many equity and index options. John decided to close the
|
||
trade. Nobody ever went broke taking a profit.
|
||
The trade in this example was profitable. Of course, this will not always
|
||
be the case. Sometimes short straddles will be losers—sometimes big ones.
|
||
Big moves and rising implied volatility can be perilous to short straddles
|
||
and their writers. If the XYZ stock in the previous example had gapped up
|
||
to $115—which is not an unreasonable possibility—John’s trade would
|
||
have been ugly.
|
||
Synthetic Straddles
|
||
Straddles are the pet strategy of certain professional traders who specialize
|
||
in trading volatility. In fact, in the mind of many of these traders, a straddle
|
||
is all there is. Any single-legged trade can be turned into a straddle
|
||
synthetically simply by adding stock.
|
||
Chapter 6 discussed put-call parity and showed that, for all intents and
|
||
purposes, a put is a call and a call is a put. For the most part, the greeks of
|
||
the options in the put-call pair are essentially the same. The delta is the only
|
||
real difference. And, of course, that can be easily corrected. As a matter of
|
||
perspective, one can make the case that buying two calls is essentially the
|
||
same as buying a call and a put, once stock enters into the equation.
|
||
Take a non-dividend-paying stock trading at $40 a share. With 60 days
|
||
until expiration, a 25 volatility, and a 4 percent interest rate, the greeks of
|
||
the 40-strike calls and puts of the straddle are as follows:
|
||
Essentially, the same position can be created by buying one leg of the
|
||
spread synthetically. For example, in addition to buying one 40 call, another
|
||
40 call can be purchased along with shorting 100 shares of stock to create a
|
||
40 put synthetically.
|
||
|
||
Combined, the long call and the synthetic long put (long call plus short
|
||
stock) creates a synthetic straddle. A long synthetic straddle could have
|
||
similarly been constructed with a long put and a long synthetic call (long
|
||
put plus long stock). Furthermore, a short synthetic straddle could be
|
||
created by selling an option with its synthetic pair.
|
||
Notice the similarities between the greeks of the two positions. The
|
||
synthetic straddle functions about the same as a conventional straddle.
|
||
Because the delta and gamma are nearly the same, the up-and-down risk is
|
||
nearly the same. Time and volatility likewise affect the two trades about the
|
||
same. The only real difference is that the synthetic straddle might require a
|
||
bit more cash up front, because it requires buying or shorting the stock. In
|
||
practice, straddles will typically be traded in accounts with retail portfolio
|
||
margining or professional margin requirements (which can be similar to
|
||
retail portfolio margining). So the cost of the long stock or margin for short
|
||
stock is comparatively small.
|
||
Long Strangle
|
||
Definition : Buying one call and one put in the same option class, in the
|
||
same expiration cycle, but with different strike prices. Typical long
|
||
strangles involve an OTM call and an OTM put. A strangle in which an
|
||
ITM call and an ITM put are purchased is called a long guts strangle.
|
||
A long strangle is similar to a long straddle in many ways. They both
|
||
require buying a call and a put on the same class in the same expiration
|
||
month. They are both buying volatility. There are, however, some functional
|
||
differences. These differences stem from the fact that the options have
|
||
different strike prices.
|
||
Because there is distance between the strike prices, from an at-expiration
|
||
perspective, the underlying must move more for the trade to show a profit.
|
||
Exhibit 15.8 illustrates the payout of options as part of a long strangle on
|
||
a $70 stock. The graph is much like that of Exhibit 15.1 , which shows the
|
||
payout of a long straddle. But the net cost here is only 1.00, compared with
|
||
4.25 for the straddle with the same time and volatility inputs. The cost is
|
||
lower because this trade consists of OTM options instead of ATM options.
|
||
The breakdown is as follows:
|
||
|
||
EXHIBIT 15.8 Long strangle at-expiration diagram.
|
||
The underlying has a bit farther to go by expiration for the trade to have
|
||
value. If the underlying is above $75 at expiration, the call is ITM and has
|
||
value. If the underlying is below $65 at expiration, the put is ITM and has
|
||
value. If the underlying is between the two strike prices at expiration both
|
||
options expire and the 1.00 premium is lost.
|
||
An important difference between a straddle and a strangle is that if a
|
||
strangle is held until expiration, its break-even points are farther apart than
|
||
those of a comparable straddle. The 70-strike straddle in Exhibit 15.1 had a
|
||
lower breakeven of $65.75 and an upper break-even of $74.25. The
|
||
comparable strangle in this example has break-even prices of $64 and $76.
|
||
But what if the strangle is not held until expiration? Then the trade’s
|
||
greeks must be analyzed. Intuitively, two OTM options (or ITM ones, for
|
||
that matter) will have lower gamma, theta, and vega than two comparable
|
||
ATM options. This has a two-handed implication when comparing straddles
|
||
and strangles.
|
||
On the one hand, from a realized volatility perspective, lower gamma
|
||
means the underlying must move more than it would have to for a straddle
|
||
to produce the same dollar gain per spread, even intraday. But on the other
|
||
hand, lower theta means the underlying doesn’t have to move as much to
|
||
cover decay. A lower nominal profit but a higher percentage profit is
|
||
generally reaped by strangles as compared with straddles.
|
||
A long strangle composed of two OTM options will also give positive
|
||
exposure to implied volatility but, again, not as much as an ATM straddle
|
||
would. Positive vega really kicks in when the underlying is close to one of
|
||
the strike prices. This is important when anticipating changes in the stock
|
||
price and in IV.
|
||
Say a trader expects implied volatility to rise as a result of higher stock
|
||
volatility. As the stock rises or falls, the strangle will move toward the price
|
||
point that offers the highest vega (the strike). With a straddle, the stock will
|
||
be moving away from the point with the highest vega. If the stock doesn’t
|
||
move as anticipated, the lower theta and vega of the strangle compared with
|
||
the ATM straddle have a less adverse effect on P&L.
|
||
Long-Strangle Example
|
||
Let’s return to Susan, who earlier in this chapter bought a straddle on Acme
|
||
Brokerage Co. (ABC). Acme currently trades at $74.80 a share with current
|
||
realized volatility at 36 percent. The stock’s volatility range for the past
|
||
month was between 36 and 47. The implied volatility of the four-week
|
||
options is 36 percent. The range over the past month for the IV of the front
|
||
month has been between 34 and 55.
|
||
As in the long-straddle example earlier in this chapter, there is a great deal
|
||
of uncertainty in brokerage stocks revolving around interest rates, credit-
|
||
default problems, and other economic issues. An FOMC meeting is
|
||
expected in about one week’s time about whose possible actions analysts’
|
||
estimates vary greatly, from a cut of 50 basis points to no cut at all. Add a
|
||
pending earnings release to the docket, and Susan thinks Acme may move
|
||
quite a bit.
|
||
In this case, however, instead of buying the 75-strike straddle, Susan pays
|
||
2.35 for 20 one-month 70–80 strangles. Exhibit 15.9 compares the greeks of
|
||
the long ATM straddle with those of the long strangle.
|
||
EXHIBIT 15.9 Long straddle versus long strangle.
|
||
The cost of the strangle, at 2.35, is about 40 percent of the cost of the
|
||
straddle. Of course, with two long options in each trade, both have positive
|
||
gamma and vega and negative theta, but the exposure to each metric is less
|
||
with the strangle. Assuming the same stock-price action, a strangle would
|
||
enjoy profits from movement and losses from lack of movement that were
|
||
similar to those of a straddle—just nominally less extreme.
|
||
For example, if Acme stock rallies $5, from $74.80 to $79.80, the gamma
|
||
of the 75 straddle will grow the delta favorably, generating a gain of 1.50,
|
||
or about 25 percent. The 70–80 strangle will make 1.15 from the curvature
|
||
of the delta–almost a 50 percent gain.
|
||
With the straddle and especially the strangle, there is one more detail to
|
||
factor in when considering potential P&L: IV changes due to stock price
|
||
movement. IV is likely to fall as the stock rallies and rise as the stock
|
||
declines. The profits of both the long straddle and the long strangle would
|
||
likely be adversely affected by IV changes as the stock rose toward $79.80.
|
||
And because the stock would be moving away from the straddle strike and
|
||
toward one of the strangle strikes, the vegas would tend to become more
|
||
similar for the two trades. The straddle in this example would have a vega
|
||
of 2.66, while the strangle’s vega would be 2.67 with the underlying at
|
||
$79.80 per share.
|
||
Short Strangle
|
||
Definition : Selling one call and one put in the same option class, in the
|
||
same expiration cycle, but with different strike prices. Typically, an OTM
|
||
call and an OTM put are sold. A strangle in which an ITM call and an ITM
|
||
put are sold is called a short guts strangle.
|
||
A short strangle is a volatility-selling strategy, like the short straddle. But
|
||
with the short strangle, the strikes are farther apart, leaving more room for
|
||
error. With these types of strategies, movement is the enemy. Wiggle room
|
||
is the important difference between the short-strangle and short-straddle
|
||
strategies. Of course, the trade-off for a higher chance of success is lower
|
||
option premium.
|
||
Exhibit 15.10 shows the at-expiration diagram of a short strangle sold at
|
||
1.00, using the same options as in the diagram for the long strangle.
|
||
EXHIBIT 15.10 Short strangle at-expiration diagram.
|
||
Note that if the underlying is between the two strike prices, the maximum
|
||
gain of 1.00 is harvested. With the stock below $65 at expiration, the short
|
||
put is ITM, with a +1.00 delta. If the stock price is below the lower
|
||
breakeven of $64 (the put strike minus the premium), the trade is a loser.
|
||
The lower the stock, the bigger the loss. If the underlying is above $75, the
|
||
short call is ITM, with a −1.00 delta. If the stock is above the upper
|
||
breakeven of $76 (the call strike plus the premium), the trade is a loser. The
|
||
higher the stock, the bigger the loss.
|
||
Intuitively, the signs of the greeks of this strangle should be similar to
|
||
those of a short straddle—negative gamma and vega, positive theta. That
|
||
means that increased realized volatility hurts. Rising IV hurts. And time
|
||
heals all wounds—unless, of course, the wounds caused by gamma are
|
||
greater than the net premium received.
|
||
This brings us to an important philosophical perspective that emphasizes
|
||
the differences between long straddles and strangles and their short
|
||
counterparts. Losses from rising vega are temporary; the time value of all
|
||
options will be zero at expiration. But gamma losses can be permanent and
|
||
profound. These short strategies have limited profit potential and unlimited
|
||
loss potential. Although short-term profits (or losses) can result from IV
|
||
changes, the real goal here is to capture theta.
|
||
Short-Strangle Example
|
||
Let’s revisit John, a Federal XYZ (XYZ) trader. XYZ is at $104.75 in this
|
||
example, with an implied volatility of 26 percent and a stock volatility of
|
||
22. Both implied and realized volatility are higher than has been typical
|
||
during the past twelve months. John wants to sell volatility. In this example,
|
||
he believes the stock price will remain in a fairly tight range, causing
|
||
realized volatility to revert to its normal level, in this case between 15 and
|
||
20 percent.
|
||
He does everything possible to ensure success. This includes scanning the
|
||
news headlines on XYZ and its financials for a reason not to sell volatility.
|
||
Playing devil’s advocate with oneself can uncover unforeseen yet valid
|
||
reasons to avoid making bad trades. John also notes the recent price range,
|
||
which has been between $111.71 and $102.05 over the past month. Once
|
||
John commits to an outlook on the stock, he wants to set himself up for
|
||
maximum gain if he’s right and, for that matter, to maximize his chances of
|
||
being right. In this case, he decides to sell a strangle to give himself as
|
||
much margin for error as possible. He sells 10 three-week 100–110
|
||
strangles at 1.80.
|
||
Exhibit 15.11 compares the greeks of this strangle with those of the 105
|
||
straddle.
|
||
EXHIBIT 15.11 Short straddle vs. short strangle.
|
||
As expected, the strangle’s greeks are comparable to the straddle’s but of
|
||
less magnitude. If John’s intention were to capture a drop in IV, he’d be
|
||
better off selling the bigger vega of the straddle. Here, though, he wants to
|
||
see the premium at zero at expiration, so the strangle serves his purposes
|
||
better. What he is most concerned about are the breakevens—in this case,
|
||
98.20 and 111.8. The straddle has closer break-even points, of $99.60 and
|
||
$110.40.
|
||
Despite the fact that in this case, John is not really trading the greeks or
|
||
IV per se, they still play an important role in his trade. First, he can use
|
||
theta to plan the best strangle to trade. In this case, he sells the three-week
|
||
strangle because it has the highest theta of the available months. The second
|
||
month strangle has a −0.71 theta, and the third month has a −0.58 theta.
|
||
With strangles, because the options are OTM, this disparity in theta among
|
||
the tradable months may not always be the case. But for this trade, if he is
|
||
still bearish on realized volatility after expiration, John can sell the next
|
||
month when these options expire.
|
||
Certainly, he will monitor his risk by watching delta and gamma. These
|
||
are his best measures of directional exposure. He will consider implied
|
||
volatility in the decision-making process, too. An implied volatility
|
||
significantly higher than the realized volatility can be a red flag that the
|
||
market expects something to happen, but there’s a bigger payoff if there is
|
||
no significant volatility. An IV significantly lower than the realized can
|
||
indicate the risk of selling options too cheaply: the premium received is not
|
||
high enough, based on how much the stock has been moving. Ideally, the
|
||
IV should be above the realized volatility by between 2 and 20 percent,
|
||
perhaps more for highly speculative traders.
|
||
Limiting Risk
|
||
The trouble with short straddles and strangles is that every once in a while
|
||
the stock unexpectedly reacts violently, moving by three or more standard
|
||
deviations. This occurs when there is a takeover, an extreme political event,
|
||
a legal action, or some other extraordinary incident. These events can be
|
||
guarded against by buying farther OTM options for protection. Essentially,
|
||
instead of selling a straddle or a strangle, one sells an iron butterfly or iron
|
||
condor. Then, when disaster strikes, it’s not a complete catastrophe.
|
||
How Cheap Is Too Cheap?
|
||
At some point, the absolute premium simply is not worth the risk of the
|
||
trade. For example, it would be unwise to sell a two-month 45–55 strangle
|
||
for 0.10 no matter what the realized volatility was. With the knowledge that
|
||
there is always a chance for a big move, it’s hard to justify risking dollars to
|
||
make a dime.
|
||
Note
|
||
1 . This depends on interest, dividends, and time to expiration. The delta
|
||
will likely not be exactly zero.
|
||
CHAPTER 16
|
||
Ratio Spreads and Complex Spreads
|
||
The purpose of spreading is to reduce risk. Buying one contract and selling
|
||
another can reduce some or all of a trade’s risks, as measured by the greeks,
|
||
compared with simply holding an outright option. But creative traders have
|
||
the ability to exercise great control over their greeks risk. They can
|
||
practically eliminate risk in some greeks, while retaining risks in just the
|
||
desired greeks. To do so, traders may have to use more complex, and less
|
||
conventional spreads. These spreads often involve buying or selling options
|
||
in quantities other than one-to-one ratios.
|
||
Ratio Spreads
|
||
The simplest versions of these strategies used by retail traders, institutional
|
||
traders, proprietary traders, and others are referred to as ratio spreads . In
|
||
ratio spreads, options are bought and sold in quantities based on a ratio. For
|
||
example, a 1:3 spread is when one option is bought (or sold) and three are
|
||
sold (or bought)—a ratio of one to three. This kind of ratio spread would be
|
||
called a “one-by-three.”
|
||
However, some option positions can get a lot more complicated. Market
|
||
makers and other professional traders manage a complex inventory of long
|
||
and short options. These types of strategies go way beyond simple at-
|
||
expiration diagrams. This chapter will discuss the two most common types
|
||
of ratio spreads—backspreads and ratio vertical spreads—and also the
|
||
delta-neutral position management of market makers and other professional
|
||
traders.
|
||
Backspreads
|
||
Definition : An option strategy consisting of more long options than short
|
||
options having the same expiration month. Typically, the trader is long calls
|
||
(or puts) in one series of options and short a fewer number of calls (or puts)
|
||
in another series with the same expiration month in the same option class.
|
||
Some traders, such as market makers, refer generically to any delta-neutral
|
||
long-gamma position as a backspread.
|
||
Shades of Gray
|
||
In its simplest form, trading a backspread is trading a one-by-two call or put
|
||
spread and holding it until expiration in hopes that the underlying stock’s
|
||
price will make a big move, particularly in the more favorable direction.
|
||
But holding a backspread to expiration as described has its challenges. Let’s
|
||
look at a hypothetical example of a backspread held to term and its at-
|
||
expiration diagram.
|
||
With the stock at $71 and one month until March expiration:
|
||
In this example, there is a credit of 3.20 from the sale of the 70 call and a
|
||
debit of 1.10 for each of the two 75 calls. This yields a total net credit of
|
||
1.00 (3.20 − 1.10 − 1.10). Let’s consider how this trade performs if it is held
|
||
until expiration.
|
||
If the stock falls below $70 at expiration, all the calls expire and the 1.00
|
||
credit is all profit. If the stock is between $70 and $75 at expiration, the 70
|
||
call is in-the-money (ITM) and the −1.00 delta starts racking up losses
|
||
above the breakeven of $71 (the strike plus the credit). At $75 a share this
|
||
trade suffers its maximum potential loss of $4. If the stock is above $75 at
|
||
expiration, the 75 calls are ITM. The net delta of +1.00, resulting from the
|
||
+2.00 deltas of the 75 calls along with the −1.00 delta of the 70 call, makes
|
||
money as the stock rises. To the upside, the trade is profitable once the
|
||
stock is at a high enough price for the gain on the two 75 calls to make up
|
||
for the loss on the 70 call. In this case, the breakeven is $79 (the $4
|
||
maximum potential loss plus the strike price of 75).
|
||
While it’s good to understand this at-expiration view of this trade, this
|
||
diagram is a bit misleading. What does the trader of this spread want to
|
||
have happen? If the trader is bearish, he could find a better way to trade his
|
||
view than this, which limits his gains to 1.00—he could buy a put. If the
|
||
trader believes the stock will make a volatile move in either direction, the
|
||
backspread offers a decidedly limited opportunity to the downside. A
|
||
straddle or strangle might be a better choice. And if the trader is bullish, he
|
||
would have to be very bullish for this trade to make sense. The underlying
|
||
needs to rise above $79 just to break even. If instead he just bought 2 of the
|
||
75 calls for 1.10, the maximum risk would be 2.20 instead of 4, the
|
||
breakeven would be $77.20 instead of $79, and profits at expiration would
|
||
rack up twice as fast above the breakeven, since the trader is net long two
|
||
calls instead of one. Why would a trader ever choose to trade a backspread?
|
||
EXHIBIT 16.1 Backspread at expiration.
|
||
The backspread is a complex spread that can be fully appreciated only
|
||
when one has a thorough knowledge of options. Instead of waiting patiently
|
||
until expiration, an experienced backspreader is more likely to gamma scalp
|
||
intermittent opportunities. This requires trading a large enough position to
|
||
make scalping worthwhile. It also requires appropriate margining (either
|
||
professional-level margin requirements or retail portfolio margining). For
|
||
example, this 1:2 contract backspread has a delta of −0.02 and a gamma of
|
||
+0.05. Fewer than 10 deltas could be scalped if the stock moves up and
|
||
down by one point. It becomes a more practical trade as the position size
|
||
increases. Of course, more practical doesn’t necessarily guarantee it will be
|
||
more profitable. The market must cooperate!
|
||
Backspread Example
|
||
Let’s say a 20:40 contract backspread is traded. (Note : In trader lingo this is
|
||
still called a one-by-two; it is just traded 20 times.) The spread price is still
|
||
1.00 credit per contract; in this case, that’s $2,000. But with this type of
|
||
trade, the spread price is not the best measure of risk or reward, as it is with
|
||
some other kinds of spreads. Risk and reward are best measured by delta,
|
||
gamma, theta, and vega. Exhibit 16.2 shows this trade’s greeks.
|
||
EXHIBIT 16.2 Greeks for 20:40 backspread with the underlying at $71.
|
||
Backspreads are volatility plays. This spread has a +1.07 vega with the
|
||
stock at $71. It is, therefore, a bullish implied volatility (IV) play. The IV of
|
||
the long calls, the 75s, is 30 percent, and that of the 70s is 32 percent. Much
|
||
as with any other volatility trade, traders would compare current implied
|
||
volatility with realized volatility and the implied volatility of recent past
|
||
and consider any catalysts that might affect stock volatility. The objective is
|
||
to buy an IV that is lower than the expected future stock volatility, based on
|
||
all available data. The focus of traders of this backspread is not the dollar
|
||
credit earned. They are more interested in buying a 30 volatility—that’s the
|
||
focus.
|
||
But the 75 calls’ IV is not the only volatility figure to consider. The short
|
||
options, the 70s, have implied volatility of 32 percent. Because of their
|
||
lower strike, the IV is naturally higher for the 70 calls. This is vertical skew
|
||
and is described in Chapter 3. The phenomenon of lower strikes in the same
|
||
option class and with the same expiration month having higher IV is very
|
||
common, although it is not always the case.
|
||
Backspreads usually involve trading vertical skew. In this spread, traders
|
||
are buying a 30 volatility and selling a 32 volatility. In trading the skew, the
|
||
traders are capturing two volatility points of what some traders would call
|
||
edge by buying the lower volatility and selling the higher.
|
||
Based on the greeks in Exhibit 16.2 , the goal of this trade appears fairly
|
||
straightforward: to profit from gamma scalping and rising IV. But, sadly,
|
||
what appears to be straightforward is not. Exhibit 16.3 shows the greeks of
|
||
this trade at various underlying stock prices.
|
||
EXHIBIT 16.3 70–75 backspread greeks at various stock prices.
|
||
Notice how the greeks change with the stock price. As the stock price
|
||
moves lower through the short strike, the 70 strike calls become the more
|
||
relevant options, outweighing the influence of the 75s. Gamma and vega
|
||
become negative, and theta becomes positive. If the stock price falls low
|
||
enough, this backspread becomes a very different position than it was with
|
||
the stock price at $71. Instead of profiting from higher implied and realized
|
||
volatility, the spread needs a lower level of both to profit.
|
||
This has important implications. First, gamma traders must approach the
|
||
backspread a little differently than they would most spreads. The
|
||
backspread traders must keep in mind the dynamic greeks of the position.
|
||
With a trade like a long straddle, in which there are no short options, traders
|
||
scalping gamma simply buy to cover short deltas as the stock falls and sell
|
||
to cover long deltas as the stock rises. The only risks are that the stock may
|
||
not move enough to cover theta or that the traders may cover deltas too
|
||
soon to maximize profits.
|
||
With the backspread, the changing gamma adds one more element of risk.
|
||
In this example, buying stock to flatten out delta as the stock falls can
|
||
sometimes be a premature move. Traders who buy stock may end up with
|
||
more long deltas than they bargained for if the stock falls into negative-
|
||
gamma territory.
|
||
Exhibit 16.3 shows that with the stock at $68, the delta for this trade is
|
||
−2.50. If the traders buy 250 shares at $68, they will be delta neutral. If the
|
||
stock subsequently falls to $62 a share, instead of being short 1.46 deltas, as
|
||
the figure indicates, they will be long 1.04 because of the 250 shares they
|
||
bought. These long deltas start to hurt as the stock continues lower.
|
||
Backspreaders must therefore anticipate stock movements to avoid
|
||
overhedging. The traders in this example may decide to lean short if the
|
||
stock shows signs of weakness.
|
||
Leaning short means that if the delta is −2.50 at $68 a share, the traders
|
||
may decide to underhedge by buying just 100 or 200 shares. If the stock
|
||
continues to fall and negative gamma kicks in, this gives the traders some
|
||
cushion to the downside. The short delta of the position moves closer to
|
||
being flat as the stock falls. Because there is a long strike and a short strike
|
||
in this delta-neutral position, trading ratio spreads is like trading a long and
|
||
a short volatility position at the same time. Trading backspreads is not an
|
||
exact science. The stock has just as good a chance of rising as it does of
|
||
falling, and if it does rise and the traders have underhedged at $68, they will
|
||
not participate in all the gains they would have if they had fully hedged by
|
||
buying 250 shares of stock. If trading were easy, everyone would do it!
|
||
Backspreaders must also be conscious of the volatility of each leg of the
|
||
spread. There is an inherent advantage in this example to buying the lower
|
||
volatility of the 75 calls and selling the higher volatility of the 70 calls. But
|
||
there is also implied risk. Equity prices and IV tend to have an inverse
|
||
relationship. When stock prices fall—especially if the drop happens quickly
|
||
—IV will often rise. When stock prices rise, IV often falls.
|
||
In this backspread example, as the stock price falls to or through the short
|
||
strike, vega becomes negative in the face of a potentially rising IV. As the
|
||
stock price rises into positive vega turf, there is the risk of IV’s declining. A
|
||
dynamic volatility forecast should be part of a backspread-trading plan. One
|
||
of the volatility questions traders face in this example is whether the two-
|
||
point volatility skew between the two strike prices is enough to compensate
|
||
for the potential adverse vega move as the stock price changes.
|
||
Put backspreads have the opposite skew/volatility issues. Buying two
|
||
lower-strike puts against one higher-strike put means the skew is the other
|
||
direction—buying the higher IV and selling the lower. The put backspread
|
||
would have long gamma/vega to the downside and short gamma/vega to the
|
||
upside. But if the vega firms up as the stock falls into positive-vega
|
||
territory, it would be in the trader’s favor. As the stock rises, leading to
|
||
negative vega, there is the potential for vega profits if IV indeed falls. There
|
||
are a lot of things to consider when trading a backspread. A good trader
|
||
needs to think about them all before putting on the trade.
|
||
Ratio Vertical Spreads
|
||
Definition : An option strategy consisting of more short options than long
|
||
options having the same expiration month. Typically, the trader is short calls
|
||
(or puts) in one series of options and long a fewer number of calls (or puts)
|
||
in another series in the same expiration month on the same option class.
|
||
A ratio vertical spread, like a backspread, involves options struck at two
|
||
different prices—one long strike and one short. That means that it is a
|
||
volatility strategy that may be long or short gamma or vega depending on
|
||
where the underlying price is at the time. The ratio vertical spread is
|
||
effectively the opposite of a backspread. Let’s study a ratio vertical using
|
||
the same options as those used in the backspread example.
|
||
With the stock at $71 and one month until March expiration:
|
||
In this case, we are buying one ITM call and selling two OTM calls. The
|
||
relationship of the stock price to the strike price is not relevant to whether
|
||
this spread is considered a ratio vertical spread. Certainly, all these options
|
||
could be ITM or OTM at the time the trade is initiated. It is also not
|
||
important whether the trade is done for a debit or a credit. If the stock price,
|
||
time to expiration, volatility, or number of contracts in the ratio were
|
||
different, this could just as easily been a credit ratio vertical.
|
||
Exhibit 16.4 illustrates the payout of this strategy if both legs of the 1:2
|
||
contract are still open at expiration.
|
||
EXHIBIT 16.4 Short ratio spread at expiration.
|
||
This strategy is a mirror image of the backspread discussed previously in
|
||
this chapter. With limited risk to the downside, the maximum loss to the
|
||
trade is the initial debit of 1 if the stock is below $70 at expiration and all
|
||
the calls expire. There is a maximum profit potential of 4 if the stock is at
|
||
the short strike at expiration. There is unlimited loss potential, since a short
|
||
net delta is created on the upside, as one short 75 call is covered by the long
|
||
70 call, and one is naked. The breakevens are at $71 and $79.
|
||
Low Volatility
|
||
With the stock at $71, gamma and vega are both negative. Just as the
|
||
backspread was a long volatility play at this underlying price, this ratio
|
||
vertical is a short-vol play here. As in trading a short straddle, the name of
|
||
the game is low volatility—meaning both implied and realized.
|
||
This strategy may require some gamma hedging. But as with other short
|
||
volatility delta-neutral trades, the fewer the negative scalps, the greater the
|
||
potential profit. Delta covering should be implemented in situations where
|
||
it looks as if the stock will trend deep into negative-gamma territory.
|
||
Murphy’s Law of trading dictates that delta covering will likely be wrong at
|
||
least as often as it is right.
|
||
Ratio Vertical Example
|
||
Let’s examine a trade of 20 contracts by 40 contracts. Exhibit 16.5 shows
|
||
the greeks for this ratio vertical.
|
||
EXHIBIT 16.5 Short ratio vertical spread greeks.
|
||
Before we get down to the nitty-gritty of the mechanics and management
|
||
of this trade—the how—let’s first look at the motivations for putting the
|
||
trade on—the why. For the cost of 1.00 per spread, this trader gets a
|
||
leveraged position if the stock rises moderately. The profits max out with
|
||
the stock at the short-strike target price—$75—at expiration.
|
||
Another possible profit engine is IV. Because of negative vega, there is
|
||
the chance of taking a quick profit if IV falls in the interim. But short-term
|
||
losses are possible, too. IV can rise, or negative gamma can hurt the trader.
|
||
Ultimately, having naked calls makes this trade not very bullish. A big
|
||
move north can really hurt.
|
||
Basically, this is a delta-neutral-type short-volatility play that wins the
|
||
most if the stock is at $75 at expiration. One would think about making this
|
||
trade if the mechanics fit the forecast. If this trader were a more bullish than
|
||
indicated by the profit and loss diagram, a more-balanced bull call spread
|
||
would be a better strategy, eliminating the unlimited upside risk. If upside
|
||
risk were acceptable, this trader could get more aggressive by trading the
|
||
spread one-by-three. That would result in a credit of 0.05 per spread. There
|
||
would then be no ultimate risk below $70 but rather a 0.05 gain. With
|
||
double the naked calls, however, there would be double punishment if the
|
||
stock rallied strongly beyond the upside breakeven.
|
||
Ultimately, mastering options is not about mastering specific strategies.
|
||
It’s about having a thorough enough understanding of the instrument to be
|
||
flexible enough to tailor a position around a forecast. It’s about minimizing
|
||
the unwanted risks and optimizing exposure to the intended risks. Still,
|
||
there always exists a trade-off in that where there is the potential for profit,
|
||
there is the possibility of loss—you can always be wrong.
|
||
Recalling the at-expiration diagram and examining the greeks, the best-
|
||
case scenario is intuitive: the stock at $75 at expiration. The biggest theta
|
||
would be right at that strike. But that strike price is also the center of the
|
||
biggest negative gamma. It is important to guard against upward movement
|
||
into negative delta territory, as well as movement lower where the position
|
||
has a slightly positive delta. Exhibit 16.6 shows what happens to the greeks
|
||
of this trade as the stock price moves.
|
||
EXHIBIT 16.6 Ratio vertical spread at various prices for the underlying.
|
||
As the stock begins to rise from $71 a share, negative deltas grow fast in
|
||
the short term. Careful trend monitoring is necessary to guard against a
|
||
rally. The key, however, is not in knowing what will happen but in skillfully
|
||
hedging against the unknown. The talented option trader is a disciplined
|
||
risk manager, not a clairvoyant.
|
||
One of the risks that the trader willingly accepted when placing this trade
|
||
was short gamma. But when the stock moves and deltas are created,
|
||
decisions have to be made. Did the catalyst(s)—if any—that contributed to
|
||
the rise in stock price change the outlook for volatility? If not, the decision
|
||
is simply whether or not to hedge by buying stock. However, if it appears
|
||
that volatility is on the rise, it is not just a delta decision. A trader may
|
||
consider buying some of the short options back to reduce volatility
|
||
exposure.
|
||
In this example, if the stock rises and it’s feared that volatility may
|
||
increase, a good choice may be to buy back some of the short 75-strike
|
||
calls. This has the advantage of reducing delta (buy enough deltas to flatten
|
||
out) and reducing gamma and vega. Of course, the downside to this strategy
|
||
is that in purchasing the calls, a loss is likely to be locked in. Unless a lot of
|
||
time has passed or implied volatility has dropped sharply, the calls will
|
||
probably be bought at a higher price than they were sold.
|
||
If the stock makes a violent move upward, a loss will be incurred.
|
||
Whether this loss is locked in by closing all or part of the position, the
|
||
account will still be down in value. The decision to buy the calls back at a
|
||
loss is based on looking forward. Nothing good can come of looking back.
|
||
How Market Makers Manage
|
||
Delta-Neutral Positions
|
||
While market makers are not position traders per se, they are expert
|
||
position managers. For the most part, market makers make their living by
|
||
buying the bid and selling the offer. In general, they don’t act; they react.
|
||
Most of their trades are initiated by taking the other side of what other
|
||
people want to do and then managing the risk of the positions they
|
||
accumulate.
|
||
The business of a market maker is much like that of a casino. A casino
|
||
takes the other side of people’s bets and, in the long run, has a statistical
|
||
(theoretical) edge. For market makers, because theoretical value resides in
|
||
the middle of the bid and the ask, these accommodating trades lead to a
|
||
theoretical profit—that is, the market maker buys below theoretical value
|
||
and sells above. Actual profit—cold, hard cash you can take to the bank—
|
||
is, however, dependent on sound management of the positions that are
|
||
accumulated.
|
||
My career as a market maker was on the floor of the Chicago Board
|
||
Options Exchange (CBOE) from 1998 to 2005. Because, over all, the trades
|
||
I made had a theoretical edge, I hoped to trade as many contracts as
|
||
possible on my markets without getting too long or too short in any option
|
||
series or any of my greeks.
|
||
As a result of reacting to order flow, market makers can accumulate a
|
||
large number of open option series for each class they trade, resulting in a
|
||
single position. For example, Exhibit 16.7 shows a position I had in Ford
|
||
Motor Co. (F) options as a market maker.
|
||
EXHIBIT 16.7 Market-maker position in Ford Motor Co. options.
|
||
|
||
With all the open strikes, this position is seemingly complex. There is not
|
||
a specific name for this type of “spread.” The position was accumulated
|
||
over a long period of time by initiating trades via other traders selling
|
||
options to me at prices I wanted to buy them—my bid—and buying options
|
||
from me at prices I wanted to sell them—my offer. Upon making an option
|
||
trade, I needed to hedge directional risk immediately. I usually did so by
|
||
offsetting my option trades by taking the opposite delta position in the stock
|
||
—especially on big-delta trades. Through this process of providing liquidity
|
||
to the market, I built up option-centric risk.
|
||
To manage this risk I needed to watch my other greeks. To be sure, trying
|
||
to draw a P&L diagram of this position would be a fruitless endeavor.
|
||
Exhibit 16.8 shows the risk of this trade in its most distilled form.
|
||
EXHIBIT 16.8 Analytics for market-maker position in Ford Motor Co.
|
||
(stock at $15.72).
|
||
Delta +1,075
|
||
Gamma−10,191
|
||
Theta +1,708
|
||
Vega +7,171
|
||
Rho −33,137
|
||
The +1,075 delta shows comparatively small directional risk relative to
|
||
the −10,191 gamma. Much of the daily task of position management would
|
||
be to carefully guard against movement by delta hedging when necessary to
|
||
earn the $1,708 per day theta.
|
||
Much of the negative gamma/positive theta comes from the combined
|
||
1,006 short January 15 calls and puts. (Note that because this position is
|
||
traded delta neutral, the net long or short options at each strike is what
|
||
matters, not whether the options are calls or puts. Remember that in delta-
|
||
neutral trading, a put is a call, and a call is a put.) The positive vega stems
|
||
from the fact that the position is long 1,927 January 2003 20-strike options.
|
||
Although this position has a lot going on, it can be broken down many
|
||
ways. Having long LEAPS options and short front-month options gives this
|
||
position the feel of a time spread. One way to think of where most of the
|
||
gamma risk is coming from is to bear in mind that the 15 strike is
|
||
synthetically short 503 straddles (1,006 options ÷ two). But this position
|
||
overall is not like a straddle. There are more strikes involved—a lot more.
|
||
There is more short gamma to the downside if the price of Ford falls toward
|
||
$12.50. To the upside, the 17.50 strike is long a combined total of 439
|
||
options. Looking at just the 15 and 17.50 strikes, we can see something that
|
||
looks more like a ratio spread: 1,006:439. If the stock were at $17.50, the
|
||
gamma would be around +5,000.
|
||
With the stock at $15.72, there is realized volatility risk of F rallying, but
|
||
with gamma changing from negative to positive as the stock rallies, the risk
|
||
of movement decreases quickly. The 20 strike is short 871 options which
|
||
brings the position back to negative-gamma territory. Having alternating
|
||
long and short strikes, sometimes called a butterflied position, is a handy
|
||
way for market makers to reduce risk. A position is perfectly butterflied if it
|
||
has alternating long and short strikes with the same number of contracts.
|
||
Through Your Longs to Your Shorts
|
||
With market-maker-type positions consisting of many strikes, the greatest
|
||
profit is gained if the underlying security moves through the longs to the
|
||
shorts. This provides kind of a win-win scenario for greeks traders. In this
|
||
situation, traders get the benefit of long gamma as the stock moves higher
|
||
or lower through the long strike. They also reap the benefits of theta when
|
||
the stock sits at the short strike.
|
||
Trading Flat
|
||
Most market makers like to trade flat—that is, profit from the bid-ask
|
||
spread and strive to lower exposure to direction, time, volatility, and interest
|
||
as much as possible. But market makers are at the mercy of customer
|
||
orders, or paper, as it’s known in the industry. If someone sells, say, the
|
||
March 75 calls to a market maker at the bid, the best-case scenario is that
|
||
moments later someone else buys the same number of the same calls—the
|
||
March 75s, in this case—from that same market maker at the offer. This is
|
||
locking in a profit.
|
||
Unfortunately, this scenario seldom plays out this way. In my seven years
|
||
as a market maker, I can count on one hand the number of times the option
|
||
gods smiled upon me in such a way as to allow me to immediately scalp an
|
||
option. Sometimes, the same option will not trade again for a week or
|
||
longer. Very low-volume options trade “by appointment only.” A market
|
||
maker trading illiquid options may hold the position until it expires, having
|
||
no chance to get out at a reasonable price, often taking a loss on the trade.
|
||
More typically, if a market maker buys an option, he must sell a different
|
||
option to lessen the overall position risk. The skills these traders master are
|
||
to lower bids and offers on options when they are long gamma and/or vega
|
||
and to raise bids and offers on options when they are short gamma and/or
|
||
vega. This raising and lowering of markets is done to manage risk.
|
||
Effectively, this is your standard high school economics supply-and-
|
||
demand curves in living color. When the market demands (buys) all the
|
||
options that are supplied (offered) at a certain price, the price rises. When
|
||
the market supplies (sells) all the options demanded (bid) at a price level,
|
||
the price falls. The catalyst of supply and demand is the market maker and
|
||
his risk tolerance. But instead of the supply and demand for individual
|
||
options, it is supply and demand for gamma, theta, and vega. This is trading
|
||
option greeks.
|
||
Hedging the Risk
|
||
Delta is the easiest risk for floor traders to eliminate quickly. It becomes
|
||
second nature for veteran floor traders to immediately hedge nearly every
|
||
trade with the underlying. Remember, these liquidity providers are in the
|
||
business of buying option bids and selling option offers, not speculating on
|
||
direction.
|
||
The next hurdle is to trade out of the option-centric risk. This means that
|
||
if the market maker is long gamma, he needs to sell options; if he’s short
|
||
gamma, he needs to buy some. Same with theta and vega. Market makers
|
||
move their bids and offers to avoid being saddled with too much gamma,
|
||
theta, and vega risk. Experienced floor traders are good at managing option
|
||
risk by not biting off more than they can chew. They strive to never buy or
|
||
sell more options than they can spread off by selling or buying other
|
||
options. This breed of trader specializes in trading the spread and managing
|
||
risk, not in predicting the future. They’re market makers, not market takers.
|
||
Trading Skew
|
||
There are some trading strategies for which market makers have a natural
|
||
propensity that stems from their daily activity of maintaining their
|
||
positions. While money managers who manage equity funds get to know
|
||
the fundamentals of the stocks they trade very well, options market makers
|
||
know the volatility of the option classes they trade. When they adjust their
|
||
markets in reacting to order flow, it’s, mechanically, implied volatility that
|
||
they are raising or lowering to change theoretical values. They watch this
|
||
figure very carefully and trade its subtle changes.
|
||
A characteristic of options that many market makers and some other
|
||
active professional traders observe and trade is the volatility skew. Savvy
|
||
traders watch the implied volatility of the strikes above the at-the-money
|
||
(ATM)—referred to as calls , for simplicity—compared with the strikes
|
||
below the ATM, referred to as puts . In most stocks, there typically exists a
|
||
“normal” volatility skew inherent to options on that stock. When this skew
|
||
gets out of line, there may be an opportunity.
|
||
Say for a particular option class, the call that is 10 percent OTM typically
|
||
trades about four volatility points lower than the put that is 10 percent
|
||
OTM. For example, for a $50 stock, the 55 calls are trading at a 21 IV and
|
||
the 45 puts are trading at a 25 volatility. If the 45 puts become bid higher,
|
||
say, nine points above where the calls are offered—for instance, the puts are
|
||
bid at 32 volatility bid while the calls are offered at 23 vol—a trader can
|
||
speculate on the skew reverting back to its normal relationship by selling
|
||
the puts, buying the calls, and hedging the delta by selling the right amount
|
||
of stock.
|
||
This position—long a call, short a put with a different strike, and short
|
||
stock on a delta-neutral ratio—is called a risk reversal. The motive for risk
|
||
reversals is to capture vega as the skew realigns itself. But there are many
|
||
risk factors that require careful attention.
|
||
First, as in other positions consisting of both long and short strikes, the
|
||
gamma, theta, and vega of the position will vary from positive to negative
|
||
depending on the price of the underlying. Risk-reversal traders must be
|
||
prepared to trade long gamma (and battle time decay) when the stock rallies
|
||
closer to the long-call strike and trade short gamma (and assume the risk of
|
||
possible increased realized volatility) when the stock moves closer to the
|
||
short-put strike.
|
||
As for vega, being short implied volatility on the downside and long on
|
||
the upside is inherently a potentially bad position whichever way the stock
|
||
moves. Why? As equities decline in price, the implied volatility of their
|
||
options tends to rise. But the downside is where the risk reversal has its
|
||
short vega. Furthermore, as equities rally, their IV tends to fall. That means
|
||
the long vega of the upside hurts as well.
|
||
When Delta Neutral Isn’t Direction
|
||
Indifferent
|
||
Many dynamic-volatility option positions, such as the risk reversal, have
|
||
vega risk from potential IV changes resulting from the stock’s moving. This
|
||
is indirectly a directional risk. While having a delta-neutral position hedges
|
||
against the rather straightforward directional risk of the position delta, this
|
||
hidden risk of stock movement is left unhedged. In some circumstances, a
|
||
delta-lean can help abate some of the vega risk of stock-price movement.
|
||
Say an option position has fairly flat greeks at the current stock price. Say
|
||
that given the way this particular position is set up, if the stock rises, the
|
||
position is still fairly flat, but if the stock falls, short lower-strike options
|
||
will lead to negative gamma and vega. One way to partially hedge this
|
||
position is to lean short deltas—that is, instead of maintaining a totally flat
|
||
delta, have a slightly short delta. That way, if the stock falls, the trade
|
||
profits some on the short stock to partially offset some of the anticipated
|
||
vega losses. The trade-off of this hedge is that if the stock rises, the trade
|
||
loses on the short delta.
|
||
Delta leans are more of an art than a science and should be used as a
|
||
hedge only by experienced vol traders. They should be one part of a well-
|
||
orchestrated plan to trade the delta, gamma, theta, and vega of a position.
|
||
And, to be sure, a delta lean should be entered into a model for simulation
|
||
purposes before executing the trade to study the up-and-down risk of the
|
||
position. If the lean reduces the overall risk of the position, it should be
|
||
implemented. But if it creates a situation where there is an anticipated loss
|
||
if the stock moves in either direction and there is little hope of profiting
|
||
from the other greeks, the lean is not the answer—closing the position is.
|
||
Managing Multiple-Class Risk
|
||
Most traders hold option positions in more than one option class. As an
|
||
aside, I recommend doing so, capital and experience permitting. In my
|
||
experience, having positions in multiple classes psychologically allows for
|
||
a certain level of detachment from each individual position. Most traders
|
||
can make better decisions if they don’t have all their eggs in one basket.
|
||
But holding a portfolio of option positions requires one more layer of risk
|
||
management. The trader is concerned about the delta, gamma, theta, vega,
|
||
and rho not only of each individual option class but also of the portfolio as a
|
||
whole. The trader’s portfolio is actually one big position with a lot of
|
||
moving parts. To keep it running like a well-oiled machine requires
|
||
monitoring and maintaining each part to make sure they are working
|
||
together. To have the individual trades work in harmony with one another, it
|
||
is important to keep a well-balanced series of strategies.
|
||
Option trading requires diversification, just like conventional linear stock
|
||
trading or investing. Diversification of the option portfolio is easily
|
||
measured by studying the portfolio greeks. By looking at the net greeks of
|
||
the portfolio, the trader can get some idea of exposure to overall risk in
|
||
terms of delta, gamma, theta, vega, and rho.
|
||
CHAPTER 17
|
||
Putting the Greeks into Action
|
||
This book was intended to arm the reader with the knowledge of the greeks
|
||
needed to make better trading decisions. As the preface stated, this book is
|
||
not so much a how-to guide as a how-come tutorial. It is step one in a three-
|
||
step learning process:
|
||
Step One: Study . First, aspiring option traders must learn as much as
|
||
possible from books such as this one and from other sources, such as
|
||
articles, both in print and online, and from classes both in person and
|
||
online. After completing this book, the reader should have a solid base
|
||
of knowledge of the greeks.
|
||
Step Two: Paper Trade . A truly deep understanding requires practice,
|
||
practice, and more practice! Fortunately, much of this practice can be
|
||
done without having real money on the line. Paper trading—or
|
||
simulated trading—in which one trades real markets but with fake
|
||
money is step two in the learning process. I highly recommend paper
|
||
trading to kick the tires on various types of strategies and to see how
|
||
they might work differently in reality than you thought they would in
|
||
theory.
|
||
Step Three: Showtime ! Even the most comprehensive academic study
|
||
or windfall success with paper profits doesn’t give one a true feel for
|
||
how options work in the real world. There are some lessons that must
|
||
be learned from the black and the blue. When there’s real money on the
|
||
line, you will trade differently—at least in the beginning. It’s human
|
||
nature to be cautious with wealth. This is not a bad thing. But emotions
|
||
should not override sound judgment. Start small—one or two lots per
|
||
trade—until you can make rational decisions based on what you have
|
||
learned, keeping emotions in check.
|
||
This simple three-step process can take years of diligent work to get it
|
||
right. But relax. Getting rich quick is truly a poor motivation for trading
|
||
options. Option trading is a beautiful thing! It’s about winning. It’s about
|
||
beating the market. It’s about being smart. Don’t get me wrong—wealth can
|
||
be a nice by-product. I’ve seen many people who have made a lot of money
|
||
trading options, but it takes hard work. For every successful option trader
|
||
I’ve met, I’ve met many more who weren’t willing to put in the effort, who
|
||
brashly thought this is easy, and failed miserably.
|
||
Trading Option Greeks
|
||
Traders must take into account all their collective knowledge and
|
||
experience with each and every trade. Now that you’re armed with
|
||
knowledge of the greeks, use it! The greeks come in handy in many ways.
|
||
Choosing between Strategies
|
||
A very important use of the greeks is found in selecting the best strategy for
|
||
a given situation. Consider a simple bullish thesis on a stock. There are
|
||
plenty of bullish option strategies. But given a bullish forecast, which
|
||
option strategy should a trader choose? The answer is specific to each
|
||
unique opportunity. Trading is situational.
|
||
Example 1
|
||
Imagine a trader, Arlo, is studying the following chart of Agilent
|
||
Technologies Inc. (A). See Exhibit 17.1 .
|
||
EXHIBIT 17.1 Agilent Technologies Inc. daily candles.
|
||
Source : Chart courtesy of Livevol® Pro ( www.livevol.com )
|
||
The stock has been in an uptrend for six weeks or so. Close-to-close
|
||
volatility hasn’t increased much. But intraday volatility has increased
|
||
greatly as indicated by the larger candles over the past 10 or so trading
|
||
sessions. Earnings is coming up in a week in this example, however implied
|
||
volatility has not risen much. It is still “cheap” relative to historical
|
||
volatility and past implied volatility. Arlo is bullish. But how does he play
|
||
it? He needs to use what he knows about the greeks to guide his decision.
|
||
Arlo doesn’t want to hold the trade through earnings, so it will be a short-
|
||
term trade. Thus, theta is not much of a concern. The low-priced volatility
|
||
guides his strategy selection in terms of vega. Arlo certainly wouldn’t want
|
||
a short-vega trade. Not with the prospect of implied volatility potential
|
||
rising going into earnings. In fact, he’d actually want a big positive vega
|
||
position. That rules out a naked/cash-secured put, put credit spread and the
|
||
likes.
|
||
He can probably rule out vertical spreads all together. He doesn’t need to
|
||
spread off theta. He doesn’t want to spread off vega. Positive gamma is
|
||
attractive for this sort of trade. He wouldn’t want to spread that off either.
|
||
Plus, the inherent time component of spreads won’t work well here. As
|
||
discussed in Chapter 9, the bulk of vertical spreads profits (or losses) take
|
||
time to come to fruition. The deltas of a call spread are smaller than an
|
||
outright call. Profits would come from both delta and theta, if the stock rises
|
||
to the short strike and positive theta kicks in.
|
||
The best way for Arlo to play this opportunity is by buying a call. It gives
|
||
him all the greeks attributes he wants (comparatively big positive delta,
|
||
gamma and vega) and the detriment (negative theta) is not a major issue.
|
||
He’d then select among in-the-money (ITM), at-the-money (ATM), and
|
||
out-of-the-money (OTM) calls and the various available expiration cycles.
|
||
In this case, because positive gamma is attractive and theta is not an issue,
|
||
he’d lean toward a front month (in this case, three week) option. The front
|
||
month also benefits him in terms of vega. Though the vegas are smaller for
|
||
short-term options, if there is a rise in implied volatility leading up to
|
||
earnings, the front month will likely rise much more than the rest. Thus, the
|
||
trader has a possibility for profits from vega.
|
||
Example 2
|
||
A trader, Luke, is studying the following chart for United States Steel Corp.
|
||
(X). See Exhibit 17.2 .
|
||
EXHIBIT 17.2 United States Steel Corp. daily candles.
|
||
Source : Chart courtesy of Livevol® Pro ( www.livevol.com )
|
||
This stock is in a steady uptrend, which Luke thinks will continue.
|
||
Earnings are out and there are no other expected volatility events on the
|
||
horizon. Luke thinks that over the next few weeks, United States Steel can
|
||
go from its current price of around $31 a share to about $34. Volatility is
|
||
midpriced in this example—not cheap, not expensive.
|
||
This scenario is different than the previous one. Luke plans to potentially
|
||
hold this trade for a few weeks. So, for Luke, theta is an important concern.
|
||
He cares somewhat about volatility, too. He doesn’t necessarily want to be
|
||
long it in case it falls; he doesn’t want to be short it in case it rises. He’d
|
||
like to spread it off; the lower the vega, the better (positive or negative).
|
||
Luke really just wants delta play that he can hold for a few weeks without
|
||
all the other greeks getting in the way.
|
||
For this trade, Luke would likely want to trade a debit call spread with the
|
||
long call somewhat ITM and the short call at the $34 strike. This way, Luke
|
||
can start off with nearly no theta or vega. He’ll retain some delta, which
|
||
will enable the spread to profit if United States Steel rises and as it
|
||
approaches the 34 strike, positive theta will kick in.
|
||
This spread is superior to a pure long call because of its optimized greeks.
|
||
It’s superior to an OTM bull put spread in its vega position and will likely
|
||
produce a higher profit with the strikes structured as such too, as it would
|
||
have a bigger delta.
|
||
Integrating greeks into the process of selecting an option strategy must
|
||
come natural to a trader. For any given scenario, there is one position that
|
||
best exploits the opportunity. In any option position, traders need to find the
|
||
optimal greeks position.
|
||
Managing Trades
|
||
Once the trade is on, the greeks come in handy for trade management. The
|
||
most important rule of trading is Know Thy Risk . Knowing your risk means
|
||
knowing the influences that expose your position to profit or peril in both
|
||
absolute and incremental terms. At-expiration diagrams reveal, in no
|
||
uncertain terms, what the bottom-line risk points are when the option
|
||
expires. These tools are especially helpful with simple short-option
|
||
strategies and some long-option strategies. Then traders need the greeks.
|
||
After all, that’s what greeks are: measurements of option risk. The greeks
|
||
give insight into a trade’s exposure to the other pricing factors. Traders must
|
||
know the greeks of every trade they make. And they must always know the
|
||
net-portfolio greeks at all times. These pricing factors ultimately determine
|
||
the success or failure of each trade, each portfolio, and eventually each
|
||
trader.
|
||
Furthermore, always—and I do mean always—traders must know their up
|
||
and down risk, that is, the directional risk of the market moving up or down
|
||
certain benchmark intervals. By definition, moves of three standard
|
||
deviations or more are very infrequent. But they happen. In this business
|
||
anything can happen. Take the “flash crash of 2010 in which the Dow Jones
|
||
Industrial Average plunged more than 1,000 points in “a flash.” In my
|
||
trading career, I’ve seen some surprises. Traders have to plan for the worst.
|
||
It’s not too hard to tell your significant other, “Sorry I’m late, but I hit
|
||
unexpected traffic. I just couldn’t plan for it.” But to say, “Sorry, I lost our
|
||
life savings, and the kids’ college fund, and our house because the market
|
||
made an unexpected move. I couldn’t plan for it,” won’t go over so well.
|
||
The fact is, you can plan for it. And as an option trader, you have to. The
|
||
bottom line is, expect the unexpected because the unexpected will
|
||
sometimes happen. Traders must use the greeks and up and down risk,
|
||
instead of relying on other common indicators, such as the HAPI.
|
||
The HAPI: The Hope and Pray
|
||
Index
|
||
So you bought a call spread. At the opening bell the next morning, you find
|
||
that the market for the underlying has moved lower—a lot lower. You have
|
||
a loss on your hands. What do you do? Keep a positive attitude? Wear your
|
||
lucky shirt? Pray to the options gods? When traders finds themselves
|
||
hoping and praying—I swear I’ll never do that again if I can just get out of
|
||
this position!—it is probably time for them to take their losses and move on
|
||
to the next trade. The Hope and Pray Index is a contraindicator. Typically,
|
||
the higher it is, the worse the trade.
|
||
There are two numbers a trader can control: the entry price and the exit
|
||
price. All of the other flashing green and red numbers on the screen are out
|
||
of the trader’s control. Savvy traders observe what the market does and
|
||
make decisions on whether and when to enter a position and when to exit.
|
||
Traders who think about their positions in terms of probability make better
|
||
decisions at both of these critical moments.
|
||
In entering a trade, traders must consider their forecast, their assessment
|
||
of the statistical likelihood of success, the potential payout and loss, and
|
||
their own tolerance for risk. Having considered these criteria helps the
|
||
traders stay the course and avoid knee-jerk reactions when the market
|
||
moves in the wrong direction. Trading is easy when positions make money.
|
||
It is how traders deal with adverse positions that separates good traders
|
||
from bad.
|
||
Good traders are good at losing money. They take losses quickly and let
|
||
profits run. Accepting, before entering the trade, the statistical nature of
|
||
trading can help traders trade their positions with less emotion. It then
|
||
becomes a matter of competent management of those positions based on
|
||
their knowledge of the factors affecting option values: the greeks. Learning
|
||
to think in terms of probability is among the most difficult challenges for a
|
||
new options trader.
|
||
Chapter 5 discussed my Would I Do It Now? Rule, in which a trader asks
|
||
himself: if I didn’t currently have this position, would I put it on now at
|
||
current market prices? This rule is a handy technique to help traders filter
|
||
out the noise in their heads that clouds judgment and to help them to make
|
||
rational decisions on whether to hold a position, close it out or adjust it.
|
||
Adjusting
|
||
Sometimes the position a trader starts off with is not the position he or she
|
||
should have at present. Sometimes positions need to be changed, or
|
||
adjusted, to reflect current market conditions. Adjusting is very important to
|
||
option traders. To be good at adjusting, traders need to use the greeks.
|
||
Imagine a trader makes the following trade in Halliburton Company
|
||
(HAL) when the stock is trading $36.85.
|
||
Sell 10 February 35–36–38–39 iron condors at 0.45
|
||
February has 10 days until expiration in this example. The greeks for this
|
||
trade are as follows:
|
||
Delta: −6.80
|
||
Gamma: −119.20
|
||
Theta: +21.90
|
||
Vega: −12.82
|
||
The trader has a neutral outlook, which can be inferred by the near-flat
|
||
delta. But what if the underlying stock begins to rise? Gamma starts kicking
|
||
in. The trader can end up with a short-biased delta that loses exponentially
|
||
if the stock continues to climb. If Halliburton rises (or falls for that matter)
|
||
the trader needs to recalibrate his outlook. Surely, if the trader becomes
|
||
bullish based on recent market activity, he’d want to close the trade. If the
|
||
trader is bearish, he’d probably let the negative delta go in hopes of making
|
||
back what was lost from negative gamma. But what if the trader is still
|
||
neutral?
|
||
A neutral trader needs a position that has greeks which reflect that
|
||
outlook. The trader would want to get delta back towards zero. Further,
|
||
depending on how much the stock rises, theta could start to lose its benefit.
|
||
If Halliburton approaches one of the long strikes, theta could move toward
|
||
zero, negating the benefit of this sort of trade all together. If after the stock
|
||
rises, the trader is still neutral at the new underlying price level, he’d likely
|
||
adjust to get delta and theta back to desired territory.
|
||
A common adjustment in this scenario is to roll the call-credit-spread legs
|
||
of the iron condor up to higher strikes. The trader would buy ten 38 calls
|
||
and sell ten 39 calls to close the credit spread. Then the trader would buy 10
|
||
of the 39 calls as sell 10 of the 40 calls to establish an adjusted position that
|
||
is short a 10 lot of the February 35–36–39–40 iron condor.
|
||
This, of course, is just one possible adjustment a trader can make. But the
|
||
common theme among all adjustments is that the trader’s greeks must
|
||
reflect the trader’s outlook. The position greeks best describe what the
|
||
position is—that is, how it profits or loses. When the market changes it
|
||
affects the dynamic greeks of a position. If the market changes enough to
|
||
make a trader’s position greeks no longer represent his outlook, the trader
|
||
must adjust the position (adjust the greeks) to put it back in line with
|
||
expectations.
|
||
In option trading there are an infinite number of uses for the greeks. From
|
||
finding trades, to planning execution, to managing and adjusting them, to
|
||
planning exits; the greeks are truly a trader’s best resource. They help
|
||
traders see potential and actual position risk. They help traders project
|
||
potential and actual trade profitability too. Without the greeks, a trader is at
|
||
a disadvantage in every aspect of option trading. Use the greeks on each
|
||
and every trade, and exploit trades to their greatest potential.
|
||
I wish you good luck !
|
||
For me, trading option greeks has been a labor of love through the good
|
||
trades and the bad. To succeed in the long run at greeks trading—or any
|
||
endeavor, for that matter—requires enjoying the process. Trading option
|
||
greeks can be both challenging and rewarding. And remember, although
|
||
option trading is highly statistical and intellectual in nature, a little luck
|
||
never hurt! That said, good luck trading!
|
||
About the Author Dan Passarelli is an
|
||
author, trader, and former member of the
|
||
Chicago Board Options Exchange (CBOE)
|
||
and CME Group. Dan has written two books
|
||
on options trading—Trading Option Greeks
|
||
and The Market Taker’s Edge . He is also the
|
||
founder and CEO of Market Taker
|
||
Mentoring, a leading options education firm
|
||
that provides personalized, one-on-one
|
||
mentoring for option traders and online
|
||
classes. The company web site is
|
||
www.markettaker.com .
|
||
Dan began his trading career on the floor of the CBOE as an equity
|
||
options market maker. He also traded agricultural options and futures on the
|
||
floor of the Chicago Board of Trade (now part of CME Group).
|
||
In 2005, Dan joined CBOE’s Options Institute and began teaching both
|
||
basic and advanced trading concepts to retail traders, brokers, institutional
|
||
traders, financial planners and advisers, money managers, and market
|
||
makers. In addition to his work with the CBOE, he has taught options
|
||
strategies at the Options Industry Council (OIC), the International
|
||
Securities Exchange (ISE), CME Group, the Philadelphia Stock Exchange,
|
||
and many leading options-based brokerage firms. Dan has been seen on
|
||
FOX Business News and other business television programs. Dan also
|
||
contributes to financial publications such as TheStreet.com , SFO.com , and
|
||
the CBOE blog.
|
||
Dan can be reached at his web site, MarketTaker.com , or by e-mail:
|
||
dan@markettaker.com . He can be followed on Twitter at
|
||
twitter.com/Dan_Passarelli .
|
||
Index American-exercise options
|
||
Arbitrageurs
|
||
At-the-money (ATM) Backspreads
|
||
Bear call spread Bear put spread Bernanke, Ben
|
||
Black, Fischer Black-Scholes option-pricing model Boxes
|
||
building
|
||
Bull call spread strengths and limitations Bull put spread Butterflies
|
||
long
|
||
alternatives example
|
||
short
|
||
iron
|
||
long
|
||
short
|
||
Buy-to-close order Calendar spreads buying
|
||
“free” call, rolling and earning rolling the spread
|
||
income-generating, managing strength of
|
||
trading volatility term structure buying the front, selling the back
|
||
directional approach double calendars ITM or OTM
|
||
selling the front, buying the back
|
||
Calls
|
||
buying
|
||
covered
|
||
entering
|
||
exiting
|
||
long ATM
|
||
delta
|
||
gamma
|
||
rho
|
||
theta
|
||
tweaking greeks vega
|
||
long ITM
|
||
long OTM
|
||
selling
|
||
Cash settlement Chicago Board Options Exchange (CBOE) Volatility
|
||
Index®
|
||
Condors
|
||
iron
|
||
long
|
||
short
|
||
long
|
||
short
|
||
strikes
|
||
safe landing selectiveness too close
|
||
too far
|
||
with high probability of success
|
||
Contractual rights and obligations open interest and volume opening and
|
||
closing Options Clearing Corporation (OCC) standardized contracts
|
||
exercise style expiration month option series, option class, and contract size
|
||
option type
|
||
premium
|
||
quantity
|
||
strike price
|
||
Credit call spread Debit call spread Delta
|
||
dynamic inputs effect of stock price on effect of time on effect of
|
||
volatility on moneyness and Delta-neutral trading art and science
|
||
direction neutral vs. direction indifferent gamma, theta, and volatility
|
||
gamma scalping implied volatility, trading selling
|
||
portfolio margining realized volatility, trading reasons for
|
||
smileys and frowns Diagonal spreads double
|
||
Dividends
|
||
basics
|
||
and early exercise dividend plays strange deltas
|
||
and option pricing pricing model, inputting data into dates, good and bad
|
||
dividend size
|
||
Estimation, imprecision of European-exercise options Exchange-traded
|
||
fund (ETF) options Exercise style Expected volatility CBOE Volatility
|
||
Index®
|
||
implied
|
||
stock
|
||
Expiration month Ford Motor Company Fundamental analysis Gamma
|
||
dynamic
|
||
scalping
|
||
Greeks
|
||
adjusting
|
||
defined
|
||
delta
|
||
dynamic inputs effect of stock price on effect of time on effect of
|
||
volatility on moneyness and
|
||
gamma
|
||
dynamic
|
||
HAPI: Hope and Pray Index managing trades online, caveats with regard
|
||
to price vs. value rho
|
||
counterintuitive results effect of time on put-call parity
|
||
strategies, choosing between theta
|
||
effect of moneyness and stock price on effects of volatility and time
|
||
on positive or negative taking the day out
|
||
trading
|
||
vega
|
||
effect of implied volatility on effect of moneyness on effect of time
|
||
on implied volatility (IV) and
|
||
where to find Greenspan, Alan HOLDR options
|
||
Implied volatility (IV) trading
|
||
selling
|
||
and vega
|
||
In-the-money (ITM) Index options
|
||
Interest, open Interest rate moves, pricing in Intrinsic value Jelly rolls
|
||
Long-Term Equity AnticiPation Securities® (LEAPS®) Open interest
|
||
Option, definition of Option class
|
||
Option prices, measuring incremental changes in factors affecting Option
|
||
series
|
||
Options Clearing Corporation (OCC) Out-of-the-money (OTM) Parity,
|
||
definition of Pin risk
|
||
borrowing and lending money boxes
|
||
jelly rolls
|
||
Premium
|
||
Price discovery Price vs. value Pricing model, inputting data into dates,
|
||
good and bad dividend size “The Pricing of Options and Corporate
|
||
Liabilities” (Black & Scholes) Put-call parity American exercise options
|
||
essentials
|
||
dividends
|
||
synthetic calls and puts, comparing
|
||
synthetic stock strategies
|
||
theoretical value and interest rate Puts
|
||
buying
|
||
cash-secured long ATM
|
||
married
|
||
selling
|
||
Ratio spreads and complex spreads delta-neutral positions, management
|
||
by market makers through longs to shorts risk, hedging trading flat
|
||
multiple-class risk ratio spreads backspreads
|
||
vertical
|
||
skew, trading Realized volatility trading
|
||
Reversion to the mean Rho
|
||
counterintuitive results effect of time on and interest rates in planning
|
||
trades interest rate moves, pricing in LEAPS
|
||
put-call parity and time
|
||
trading
|
||
Risk and opportunity, option-specific finding the right risk long ATM call
|
||
delta
|
||
gamma
|
||
rho
|
||
theta
|
||
tweaking greeks vega
|
||
long ATM put long ITM call long OTM call options and the fair game
|
||
volatility
|
||
buying and selling direction neutral, direction biased, and direction
|
||
indifferent
|
||
Scholes, Myron Sell-to-open transaction Skew
|
||
term structure trading
|
||
vertical
|
||
Spreads
|
||
calendar
|
||
buying
|
||
“free” call, rolling and earning income-generating, managing
|
||
strength of
|
||
trading volatility term structure
|
||
diagonal
|
||
double
|
||
ratio and complex delta-neutral positions, management by market makers
|
||
multiple-class risk ratio
|
||
skew, trading
|
||
vertical
|
||
bear call
|
||
bear put
|
||
box, building bull call
|
||
bull put
|
||
credit and debit, interrelations of credit and debit, similarities in and
|
||
volatility
|
||
wing
|
||
butterflies
|
||
condors
|
||
greeks and
|
||
keys to success retail trader vs. pro trades, constructing to maximize
|
||
profit
|
||
Standard deviation and historical volatility Standard & Poor’s Depositary
|
||
Receipts (SPDRs or Spiders) Straddles
|
||
long
|
||
basic
|
||
trading
|
||
short
|
||
risks with
|
||
trading
|
||
synthetic
|
||
Strangles
|
||
long
|
||
example
|
||
short
|
||
premium
|
||
risk, limiting
|
||
Strategies and At-Expiration Diagrams buy call
|
||
buy put
|
||
factors affecting option prices, measuring incremental changes in sell call
|
||
sell put
|
||
Strike price
|
||
Supply and demand Synthetic stock strategies
|
||
conversion
|
||
market makers pin risk
|
||
reversal
|
||
Technical analysis Teenie buyers
|
||
Teenie sellers Theta
|
||
effect of moneyness and stock price on effects of volatility and time on
|
||
positive or negative risk
|
||
taking the day out Time value
|
||
Trading strategies Value
|
||
Vega
|
||
effect of implied volatility on effect of moneyness on effect of time on
|
||
implied volatility (IV) and Vertical spreads bear call
|
||
bear put
|
||
box, building bull call
|
||
bull put
|
||
credit and debit interrelations of similarities in
|
||
and volatility Volatility
|
||
buying and selling teenie buyers teenie sellers
|
||
calculating data direction neutral, direction biased, and direction
|
||
indifferent expected
|
||
CBOE Volatility Index®
|
||
implied
|
||
stock
|
||
historical (HV) standard deviation
|
||
implied (IV) and direction HV-IV divergence inertia
|
||
relationship of HV and IV
|
||
selling
|
||
supply and demand
|
||
realized
|
||
trading
|
||
skew
|
||
term structure vertical
|
||
vertical spreads and Volatility charts, studying patterns
|
||
implied and realized volatility rise realized volatility falls, implied
|
||
volatility falls realized volatility falls, implied volatility remains
|
||
constant realized volatility falls, implied volatility rises realized
|
||
volatility remains constant, implied volatility falls realized volatility
|
||
remains constant, implied volatility remains constant realized
|
||
volatility remains constant, implied volatility rises realized volatility
|
||
rises, implied volatility falls realized volatility rises, implied
|
||
volatility remains constant
|
||
Volatility-selling strategies profit potential covered call covered put
|
||
gamma-theta relationship greeks and income generation naked
|
||
call
|
||
short naked puts similarities Would I Do It Now? Rule
|
||
Volume
|
||
WeeklysSM
|
||
Wing spreads
|
||
butterflies
|
||
directional
|
||
long
|
||
short
|
||
iron
|
||
condors
|
||
iron
|
||
long
|
||
short
|
||
greeks and
|
||
keys to success retail trader vs. pro trades, constructing to maximize
|
||
profit Would I Do It Now? Rule |