IVR and Non-Traditional Diversification
Oct 4, 2017
Given the relative youth of volatility trading in the overall history of the financial markets, the term "nontraditional" fits quite well when describing the approach.
In turn, that means strategic thinking related to volatility portfolios also requires, at times, an innovative mindset.
For traders seeking to expand their thinking, a recent episode of Market Measures is worth a look. Data on the episode is presented that can help traders analyze their volatility portfolios from a fresh perspective.
Historically, the term "diversification" has been used in portfolio theory to describe the process of allocating capital such that exposure to concentrated risk is reduced.
While the practical application of this methodology certainly varies by investor, traditional diversification typically calls for the spreading of exposure across and within asset classes. Some examples of traditional portfolio diversification include:
Stocks vs. Bonds
Small cap vs. Large cap
Growth vs. Value
USA vs. International
On this episode of Market Measures, the team considers diversification as it relates to a volatility portfolio.
Volatility trading obviously revolves around implied volatility and mean reversion. In this regard, it is statistically-based, meaning that trade ideas are discovered using metrics such as Implied Volatility Rank (IVR).
IVR tells us whether implied volatility is high or low in a specific underlying based on the past year of data. For example, if implied volatility in XYZ has been between 30 and 60 during the previous 52 weeks, then an implied volatility of 45 would equate to an IVR of 50%. Likewise, an implied volatility of 60 would equate to an IVR of 100%.
At tastytrade, we look for opportunities to sell volatility when IVR is above 50%, and for opportunities to buy volatility when IVR is below 50%.
Getting back to the episode, the Market Measures team designed a study to better understand how diversification relates to a volatility portfolio. In particular, the team wondered whether focusing on a large cap index, a small cap index, or a strategy that simply selected the highest IVR (between the two), produced the best results (historically).
To arrive at an answer to this question, a study was designed that used data from 2005 to present in the SPY (large cap) and IWM (small cap). Three strategies were then backtested, all of which sold 30 delta strangles:
Portfolio 1: 100% in IWM
Portfolio 2: 100% in SPY
Portfolio 3: Whichever Index ETF (SPY or IWM) had the highest IVR at the time
It should be noted that while implied volatility is almost always higher in IWM (as compared to SPY), implied volatility rank basically benchmarks each symbol individually against itself, and therefore allows for such a study/comparison.
The results of the study, including the performance of each portfolio, are compiled in the graphic below:
Looking at the above data, it's certainly notable to see that the combined portfolio produced the most attractive results in terms of success rate, average P/L, and return on capital (ROC).
While this particular study is by no means exhaustive, the results help illustrate that "diversification" likely has a different meaning and application in the volatility niche.
While it's always important to vet an underling when trading, this study helps emphasize how the relative attractiveness of a volatility trade often centers on implied volatility metrics, such as IVR, as opposed to methods used in a more traditional portfolio.
We encourage you to watch the complete episode of Market Measures focusing on nontraditional diversification when your schedule allows.
If you have any outstanding questions or comments, please leave us a message in the space below, or reach out directly 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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