e 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.
Sta


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

eBooks\Trading Options Greeks_ How Time, Volatility, and Other Pricing Factors Drive Profits (Bloomberg Financial).pdf


ications 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 h


at 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 real


ned.
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


e 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


is 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 vol


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


mma.
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


dle.
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


lied 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


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 sho


s 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 bet


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 m


ver 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 co


ead 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