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  1. Lenn
    November 7, 2021 @ 10:06 am

    Hello,

    You say that
    “Performance of the s1 signal is explored in different contexts in other, non-paywalled s1 signal studies. In particular, different durations (0-3 DTE, 7 DTE, 45 DTE and LEAPS), different strategies (uncovered and verticals)…”

    However I could only find the two posts comparing put spreads to short puts, not any Posts comparing different DTEs.
    Is there any way to see a comparison between the different DTEs? I’d be really interested.

    Best

    Reply

    • spintwig.com
      November 7, 2021 @ 12:08 pm

      Yes! The 45 DTE version the short put study is being released this Friday. I’m also pulling together the data for the other DTEs and approaches as well. Stay tuned!

      Reply

  2. Steve Highland
    November 12, 2021 @ 11:23 am

    11-12-2021
    Hi, This may be obvious but I’m new here. I’m trying to understand what the ‘s1 signal’ is all about. I have read here: “The s1 signal is a boolean (TRUE / FALSE) daily indicator that attempts to identify the days in which short put and short vertical put positions on the S&P 500 are most likely to be profitable at expiration. s1 is based on data from CBOE and S&P Global.”
    I take it from this that it is a quant strategy based on TECHNICAL indicators, right? I realize it must be proprietary but can you please give more information on what it is and why it is likely to be reliable in order to help me understand what it is and why I should explore it further?
    Thanks!
    Steve

    Reply

    • spintwig.com
      November 20, 2021 @ 5:44 pm

      Welcome Steve — correct, the s1 signal is quantitive in nature and uses historic values to suggest when to open a position and when to sit out.

      It is reliable for several reasons:

      1) s1 uses market data as inputs – simply stated: relevant, empirical data is used. There are no “moon phases” or other nonsensical inputs.

      2) s1 data inputs are from official sources – using CBOE and S&P Global as the data providers ensures input data is as clean as possible and free from influence or error of 3rd parties

      3) s1 avoids overfitting – it’s easy to look back in time and identify an “optimal” methodology that avoids all the drawdowns. The problem with this approach is that it tunes the algo to both the signal as well as the noise in the market. The result is typically a “perfect” backtest and a poor forward-looking result. The s1 signal paints with “broad strokes” and doesn’t look for a “perfect” backtest. The result is typically a “great” backtest and a great forward-looking result.

      Hope this helps!

      Reply

  3. Dom
    November 12, 2021 @ 12:27 pm

    I’m not too sure I see the point in this, for the effort involved and time spent! I could have a 98% cash and 2% BTC portfolio that would outperform the standard buy and hold and any of these active strategies.

    You’re doing all this and not even really generating any Alpha and with a 6%+ drag from inflation right now you’re doing all this for a poultry <4% a year… kinda pathetic really.

    I think all you've proved here is that taking on the extra risk just isn't worth the returns involved.

    Reply

    • spintwig.com
      November 20, 2021 @ 5:50 pm

      I’m not too sure I see the point in this, for the effort involved and time spent! I could have a 100% BTC and 0% cash portfolio that would outperform your proposed strategy as well as buy and hold and any of these active strategies.

      Anyone can look back and say what would have made more/less money. I’m not sure I see your point.

      Reply

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