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6 Comments

  1. JEI
    October 4, 2019 @ 8:52 am

    Not that it makes a huge difference here, but your commission numbers are now high. $0.65 per contract is the new new, as of this week.

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    • spintwig.com
      October 4, 2019 @ 3:44 pm

      Maybe. Given the much higher commission costs during the mid-to-late 2000s, I think the blended average of $1/trade is still an optimistic approach for at least another few years.

      I’m loving the new cost structures at IBKR, Schwab, TD and E-Trade. It’s nice to see things get shaken up.

      Reply

      • JEI
        October 4, 2019 @ 7:05 pm

        Oh interesting, the historical commission rates hadn’t occurred to me. I think I disagree. The value of the backtest is to show what you might expect your results to be going forward, so it makes sense to me to use current (or even optimistic) prices. I would also be in favor of simulating weekly and M/W expiration for years where they didn’t exist.

        Here’s something else I’ve been thinking about:
        What about a backtester that shuffles actual stock market moves? Normalize the stock prices, and shuffle them up by quarter. That way you’re defeating any curve fitting, and at the same time you’re using data that’s similar to real data rather than completely random.

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        • spintwig.com
          October 6, 2019 @ 12:11 pm

          I’ve been building a turnkey spreadsheet model for backtesting leveraged strategies that I intend to publish in the coming days via an announcement post. Commissions are fixed at $1 each way as this is how the source data in the trade logs is calculated and delivered. I can override this by building an “adjustable commission cost” feature. This should take care of the commission preference 🙂

          Interesting idea. I’m not sure I understand the intent though. One could argue a shuffled return profile of an actual underlying is the actual return profile of a hypothetical (or by chance a different actual) underlying. If the goal is to evaluate option strategy performance in aggregate as opposed to seeing isolated performance on a single underlying, we would want to execute the same strategy on multiple underlying and compare results.

          This probably is a good segway into the scorecard I’ll be publishing and announcing in the next update post.

          Reply

  2. Pushpaw
    October 16, 2019 @ 7:51 pm

    Question: what does removing the effects of leverage from an options backtest demonstrate? I’m not a mathematician. The whole point of options is leverage, right? So…if you take that out, then what is being demonstrated. I ask because I’m wondering what I’m missing here that I should be taking away…

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    • spintwig.com
      October 17, 2019 @ 1:21 pm

      Not necessarily. For most retail traders it is indeed about leverage. However, options also serve as hedging instruments and tools to potentially lower portfolio volatility. The latter is the chief focus when it comes to mitigating sequence of returns risk.

      For our purposes here:

      -It demonstrates performance in a non-margin account such as US-based retirement accounts and other cash-secured scenarios around the world.

      -It allows us to identify which strategy is worth leveraging. Because applying leverage [usually negatively] impacts the Sharpe ratio due to the friction costs and mechanics of leverage, we want to identify strategies that already outperform the underlying on a risk-adjusted basis before scaling up.

      -It allows us to compare an option strategy against a non-leveraged buy/hold portfolio of different asset allocations. For example, if a traditional 80/20 stock/bond portfolio matches the Sharpe ratio of a non-leveraged option strategy, we can then ask which yields a greater return.

      Now that I finally have the backtest builder launched, we can start plugging in the risk-adjusted winners and see how they stack up. Tomorrow’s post will be the first to include results from the new backtest builder. I’ll be eager to hear your thoughts and feedback.

      Reply

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