After a fairly muted start to trading in 2019 (in terms of volatility), movement in the markets has finally picked up during the first couple weeks of May. This culminated in a fairly extensive selloff on May 13th, which saw the Dow Jones and S&P 500 each drop roughly 2.5%.

While recent volatility may be attributable to stalling trade war negotiations between the United States and China, it may actually be due to something else. For example, the mere fact that equity markets were back on all-time highs, or another market-related narrative that hasn't yet been widely circulated.

But as we discussed in a recent blog post “Game of Tariffs,”the exact reason for recent volatility doesn't really matter. Especially for those traders that focus almost exclusively on statistics and probabilities. For that group, the fact that the VIX went higher was likely enough reason to increase exposure to short premium.

And if you're looking for additional insight on how heightened volatility can offer potentially attractive opportunities for your portfolio, then a pair of new episodes from the Market Measures series are certainly worth a few minutes of your time.

The focus of these two episodes is "average moves," and more specifically, how implied volatility tends to be overstated when compared against "actual volatility" (aka historical volatility or realized volatility). The hardest hitting part of this two-episode series is how the Market Measures team highlights historical data focusing on this topic which spans two different trading environments - a more muted market vs. a more volatile market.

Looking at Episode 1 of the two-episode set, the Market Measures team first runs a backtest to establish how implied volatility has consistently outpaced actual volatility in SPY. In this particular study, the team reviewed the last 14 years of trading data and backtested a short strangle in SPY to establish just how much implied volatility outpaced actual volatility (on average) over those years.

The unique aspect to the analysis was that instead of looking at pure implied volatility, the team instead translated the findings into "breakeven ranges." For example, if we sell a strangle in SPY, we know exactly where our breakeven points lie for an upside or downside move in SPY. That data can be expressed as a percent move.

For the purposes of consistency, the "actual volatility" is also translated into breakeven terms, or percent moves.

The graphic below summarizes the average breakeven ranges over the 14-year period for both implied and actual volatility. As you can see, the actual move was much narrower than our threshold range for making profit (or breaking even), on average:

mm_averagemoves_190502-4.png

Based on the data above, there was on average 2.5-3% of extra room between the actual observed range and the threshold of our position for making money (or breaking even). This helps highlight the value proposition of the short premium philosophy.

A big question, especially considering the current market environment, is how that equation changes during periods of heightened volatility?

Fortunately, that was the precise focus of Episode 2.

On the second installment of Market Measures focusing on "average moves," the team next split the data into two distinct groups. The filter used to categorize the data was Implied Volatility Rank, which tends to be a good proxy for low and high volatility environments.

In this case, all instances for SPY (during that same 14-year period) in which IV Rank was below 50% were put into one group, while all instances in which IV Rank was greater than 50% were put into the other group. The same backtest from Episode 1 was then conducted a second time, on both groups of data.

The findings from this analysis were very instructive, as summarized in the slides below:

mm_averagemovespt2_190508-5.png

As you can see in the first slide above, the extra room between implied volatility and actual volatility (in breakeven terms) when IVR was below 50% was slightly lower than all instances (from Episode 1) - about 2%. That makes sense because in lower volatility environments, insurance (i.e. options) is usually priced lower, and movement also tends to be more muted.

The real surprise appears when looking at the instances in which IVR was above 50%.

As you can see in the second slide, the implied breakeven percentages widened along with the increased volatility - exactly as one might expect. What was more surprising was the fact that the “actual volatility” breakevens didn’t necessarily follow suit, at least not to the same degree.

This translated to an additional degree of “extra room” between implied and actual breakevens during these periods.

Looking only at the instances in which IV Rank was above 50%, the distance between implied and actual breakevens increased to a window of roughly 4.5 to 9% - meaning that according to historical data, the likelihood of winning on a short strangle in SPY (over the last 14 years) was actually higher when volatility was elevated!

Given the importance of this material, we hope you'll take the time to review both episodes of Market Measures focusing on implied vs. actual volatility (in terms of breakeven ranges) when your schedule allows:

If you have any questions about this material, or any other trading topic, don't hesitate to reach out with any questions on Twitter (@tastytrade) or via email (support@tastytrade.com).

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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