Leveraging the Implied Volatility-Realized Volatility Spread
Jun 20, 2018
Sometimes it's our simplest trade ideas that work the best - for example, a short straddle through earnings, or a short put in a beat-up blue chip.
Powerful analytics can at times be equally straightforward, not to mention valuable.
For some sharp new insights, we recommend a recent edition of The Ryan & Beef Show which presents fresh tastytrade research focused on the spread between implied volatility and realized volatility.
As a reminder, implied volatility represents the current market price for volatility that is "implied" by options prices, whereas realized volatility represents the actual observed volatility for a given underlying over a specified period of time in history.
In short, that means implied volatility represents what the market feels should be the price for ongoing volatility, while realized volatility can give us a sense of how "fair" that is based on recent history.
On this episode of Ryan & Beef, our dynamic duo first present a chart which illustrates the historical spread between implied volatility and realized volatility (IV-RV) from 2010 to present in SPY. A positive spread indicates that implied volatility was higher than realized volatility, while a negative spread indicates the reverse.
What's particularly remarkable about this episode is the second-level analysis conducted on the IV-RV spread, particularly as it relates to IV Rank and RV Rank.
As most are already aware, Implied Volatility Rank (IV Rank) is a tastytrade metric that provides insight on the current levels of implied volatility in a given underlying as compared to the last 52 weeks of data.
Using an example, imagine that implied volatility in symbol XYZ is trading 45 and that over the last 52 weeks it has ranged between 30 and 50. In this case, implied volatility rank would currently be 50%. If implied volatility dropped to 30, then IV Rank would drop to 0%.
Realized Volatility Rank (RV Rank) works in much the same fashion, except in this case it reports how much an underlying is actually moving as compared to the last 52 weeks of data. So if the range for realized volatility in stock ABC was between 20 and 50 over the last 52 weeks, that would mean a realized volatility of 35 would produce an RV Rank of 50%.
On their show, Ryan and Beef utilize the spread between IV Rank and RV Rank to investigate whether a short volatility strategy performed better historically when filtering only for certain levels in the spread.
Using a simple short strangle strategy, the guys backtested its historical performance using two different sets of trading conditions - one in which the difference between IV Rank and RV Rank was above 50%, and one in which the difference between IV Rank and RV Rank was below 50%.
For example, if IV Rank was 80% and RV Rank was 20%, then the difference between the two would be 60% (80%-20% = 60%). That instance would, therefore, be included in the “above 50%” filter, and so on…
Essentially, they were looking for instances in which IV Rank greatly outpaced RV Rank, and grouping them together. And doing the same for instances in which the spread between IV and RV Rank was less than 50%.
The results of that study, as depicted in the slide below, are certainly worth reviewing:
What we can see clearly in the chart above is that the success rate of the short strangle in SPY was superior when filtering for instances in which the IV-RV Rank spread was above 50%. What's even more astonishing is the dramatic increase in the profit target for instances in which the IV-RV Rank spread was above 50%, as compared to below 50%.
These findings are fairly compelling, and we recommend reviewing the complete episode of Ryan & Beef focusing on the spread between IV Rank and RV Rank when your schedule allows.
In the meantime, if you have any outstanding questions or feedback, don’t hesitate to leave us a message in the space below, or reach out via email at firstname.lastname@example.org.
We look forward to hearing from you!
Sage Anderson has an extensive background trading equity derivatives and managing volatility-based portfolios. He has traded hundreds of thousands of contracts across the spectrum of industries in the single-stock universe.
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