39 lines
3.1 KiB
Plaintext
39 lines
3.1 KiB
Plaintext
Chapter 39: Volatility Trading Techniques 815
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ing, he is generally talking about implied volatility. Thus, it makes sense to know where
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implied volatility is within the range of the past readings of implied volatility. If volatil
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ity is low with respect to where it usually trades, then we can say the options are cheap.
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Conversely, if it's high with respect to those past values, then we can say the options are
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expensive. These conclusions do not draw on historical volatility.
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The percentile of implied volatility is generally used to describe just where the
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current implied volatility reading lies with respect to its past values. The "implied
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volatility" reading that is being used in this case is the composite reading - the one
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that takes into account all the options on an underlying instrument, weighting them
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by their distance in- or out-of-the-money (at-the-money gets more weight) and also
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weighting them by their trading volume. This technique has been referred to many
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times and was first described in Chapter 28 on mathematical applications. That com
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posite implied volatility reading can be stored in a database for each underlying
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instrument every day. Such databases are available for purchase from firms that spe
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cialize in option data. Also, snapshots of such data are available to members of
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www.optionstrategist.com.
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In general, most underlying instruments would have a composite implied
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volatility reading somewhere near the 50th percentile on any given day. However, it
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is not uncommon to see some underlyings with percentile readings near zero or 100%
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on a given day. These are the ones that would interest a volatility trader. Those with
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readings in the 10th percentile or less, say, would be considered "cheap"; those in the
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90th percentile or higher would be considered expensive.
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In reality, the percentile of implied volatility is going to be affected by what the
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broad market is doing. For example, during a severe market slide, implied volatilities
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will increase across the board. Then, one may find a large number of stocks whose
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options are in the 90th percentile or higher. Conversely, there have been other times
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when overall implied volatility has declined substantially: 1993, for example, and the
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summer of 2001, for another. At those times, we often find a great number of stocks
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whose options reside in the 10th percentile of implied volatility or lower. The point
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is that the distribution of percentile readings is a dynamic thing, not something stat
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ic like a lognormal distribution. Yes, perhaps over a long period of time and taking
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into account a great number of cases, we might find that the percentiles of implied
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volatility are normally distributed, but not on any given day.
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The trader has some discretion over this percentile calculation. Foremost, he
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must decide how many days of past history he wants to use in determining the per
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centiles. There are about 255 trading days in a year. So, if he wanted a two-year his
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tory, he would record the percentile of today's composite implied volatility with
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respect to the 510 daily readings over the past two years. This author typically uses |