The goal when trading is of course to deploy positions that are consistently profitable.
The method by which many volatility traders attain this goal is through systematic, methodical decision-making. Such an approach can be utilized on the front-end, during trade filtering and analysis, as well as on the back-end, when positions are closed/exited.
At tastytrade, we often compare the performance of different position structures, trading strategies, and trade management approaches in an attempt to identify which of the variables being examined is more “efficient.”
For example, a hypothetical study to compare whether it's more efficient to sell premium in a certain type of position in "all instances,” or only when Implied Volatility Rank (IV Rank) is above 50%.
One thing to keep in mind when reviewing such analysis is that the interpretation of “efficiency” depends on the factors being evaluated. Generally speaking, efficiency speaks to the maximization of one variable versus the minimization of another (i.e. reward and risk). Hence, it’s vital to recognize which two factors are being analyzed before drawing any conclusions.
By a large margin, the two most common methods by which tastytrade evaluates “efficiency” are through the factors risk and capital.
Pertaining to risk, we normally analyze reward versus risk. And for capital, we normally analyze profit versus capital usage. In the latter case, the examination is seeking to provide insight on what produces the most reward, based on how much capital is needed to maintain the position.
In order to clarify the difference between these two perspectives on “efficiency,” the topic was featured recently on a new episode of Market Measures. The centerpiece of the show is an expansive study that speaks to “risk vs. return” and “profits vs. capital usage.”
This study was conducted in part to help traders better visualize the characteristics of each "efficiency" pairing. That way, each and every trader can better apply the findings of such studies to their own strategic approach.
While the complete parameters of the study are outlined on the episode, the general intent was to backtest historical data in SPY, and show how the results changed based on an analysis of “risk efficiency” versus an analysis of “capital efficiency.”
In that regard, the backtest was basically run twice. The first time to find the optimal delta for a historical short strangle in SPY when focusing on risk vs. reward, and the second time to find the optimal delta for a historical short strangle in SPY when focusing on profit vs. capital usage.
We hope the results, as shown in the two graphics below, will help you better understand the distinction between these two efficiency metrics. The first graphic highlights the capital efficiency results (i.e. profit vs. capital usage), while the second shows the risk efficiency results (i.e. risk vs. reward):
As you can see from the slides above, this study provides definitive clarification on the difference between the two types of “efficiency.” According to the capital efficiency analysis (the first slide), the most efficient short strangle over the last 14 years has been the 30/40 delta position.
On the other hand, based on the risk efficiency analysis (the second slide), we can see that the most efficient short strangle over the last 14 years has been a lower delta strangle - more in the range of 10/15 deltas.
The point that the Market Measures team was trying to make with this exercise is that there is no absolute measure of “efficiency,” nor is there a “perfect” strategy. Along those lines, it can’t be said that one approach is “better” than the other.
Instead, the main takeaway is that individual traders and investors must assess what metrics they want optimized and select strategies and trading approaches that best fit their own needs and goals.
We hope you’ll take the time to review the complete episode of Market Measures focusing on efficiency metrics when your schedule allows.
In the meantime, if you have any questions about this material, or any other trading-related topic, we hope you’ll reach out with any questions on Twitter (@tastytrade) or email (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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