Skip to content


  1. Madison Ruppert
    January 23, 2021 @ 4:17 pm

    I would love to see this study repeated with a shorter duration (7DTE, for example) given your other study on 50D 7DTE short puts outperforming the S&P on a risk-adjusted and total return basis. I’m wondering if that strategy was turned into a wheel strategy if it would also underperform as seen in the above study.

    Thank you for your hard work!


      January 23, 2021 @ 4:39 pm

      I can add that to the list – thanks for the suggestion!


  2. Wall Street Will Hate You for Knowing This - Crazy Finances
    January 29, 2021 @ 9:50 pm

    […] perseverance. Additionally, I don’t recommend doing this strategy on a broad index as simply buying and holding SPY would actually outperform the wheel strategy. Instead, pick a stock that you believe has long-term growth aspects and perform the strategy on […]


  3. Tim
    February 3, 2021 @ 10:14 am

    Hey, came across your posts on /r/thetagang as well as ERN. Love the backtests.

    I was wondering, how would wheeling SPY compare to wheeling a subset basket of S&P components – my curiosity is with the highest vol components.

    Component vol individually would be higher than SPY, would it be possible to structure the basket such that it has roughly the same diversified exposure of SPY whilst maintaining the benefit of higher premiums through the individual components higher vol?


      February 3, 2021 @ 7:35 pm

      Hi Tim!

      It depends how that subset basket is comprised. The more diversified the basket, the closer it’ll perform with SPY (minus the increased friction costs – contract fees, slippage – from trading a smaller amount of capital on a greater count of underlying).

      If we turn the dial toward a concentration of only high-IV underlying, I anticipate uncompensated risk with lower risk-adjusted returns; the frequency and severity of realized losses exceeding the increased premium.


  4. Vivek
    May 22, 2021 @ 3:28 pm

    How do you normalize the strategy to the benchmark (SPY)? With options strategies having so many frequent cash flows, how do you account for them while calculating the CAGR?

    Also, for calculating the Sharpe Ratio, what do you use for the rate of return?

    Basically, what I find difficult to understand is what is best way to compare buy and hold with a strategy where you keep buying and selling in indefinite intervals. Maybe something like the IRR should be used to get a more accurate picture of returns adjusting for cash flows.


      May 23, 2021 @ 8:35 pm

      One portfolio consists of buy/hold SPY and another consists of the aggregate options strategy. Each portfolio is evaluated using key performance indicators such as CAGR, Sharpe, etc. and the results are displayed.

      CAGR uses the industry standard methodology of comparing the ending and starting values and applying the respective date math.

      Sharpe ratio uses the US 3mo treasury as the risk-free rate. I have added this clarification to the methodology page at 🙂

      Transaction count and individual position duration have no bearing on the comparison mechanics since performance is measured at the portfolio level, not the individual trade level. In other words, while possible, it’s not necessary to calculate the CAGR of each individual call or put trade since aggregate performance will be captured at the portfolio level at the conclusion of the backtest.


      • Vivek
        May 23, 2021 @ 8:58 pm

        Thanks for the insight. The issue with this CAGR calculation is it does not consider the additional cash flow into the account. As SPY grew, the puts were sold at a higher and higher strike and more cash would have been inevitably pumped in to secure those puts.

        Maybe a better way would be to calculate time weighted or money weighted returns and calculate a CAGR using that?

        Here is an article that explains accounting for cash flow to calculate time weighted returns (TWR) and uses the TWR to calculate CAGR.


          May 23, 2021 @ 10:13 pm

          Ah, I see what you’re saying. That’s a very good point.

          The typical backtest I run uses hindsight bias in order to identify the minimum starting capital necessary for the backtest will run to completion whilst remaining compliant with max leverage targets / Reg-T and, of course, not turning negative. Simple enough.

          This backtest is a little different. Due to the nature of the strategy, I started with capital equal to 100 shares of underlying. If strategies begin to underperform SPY, indeed, more capital would need to be added to maintain the cash-secured nature.

          From a methodology standpoint I could either 1) track nightly cashflows needed to preserve the cash-secured nature of the strategy or 2) disregard requisite cashflows and let the backtest become necessarily theoretical as NetLiq eventually drifted below zero.

          I chose the latter. Thus, no cash flows and the CAGR methodology in use is appropriate. The results depicted are consistent with the other site-wide methodology assumptions such as margin calls never occurring and margin requirements always being satisfied. In practice the broker of course wouldn’t allow the account to continue trading with a negative balance, ignore Reg-T along the way, etc.

          I’ll look into updating future studies with cash-flow adjustments as this would be a better reflection of real-life mechanics. Nevertheless, the depicted total return and related performance is virtually identical, sans the frictions associated with contributions and distributions and interest earned on margin collateral, vs a methodology that includes nightly-cash-flow adjustments.


  5. Bob
    June 13, 2021 @ 2:16 am

    What’s up with the purple 5D line which flatlines for years?


Leave a Reply

Your email address will not be published. Required fields are marked *