Tail ratio as the best IS/OOS correlator ?

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  • #134254

    Hi Guys,

    “…tail-ratio (i.e. the ratio between the 95th and 5th percentile of the returns distribution) showed a stronger significant correlation with OOS Sharpe ratio than IS Sharpe ratio did (Pearson R² = 0.025; p < 0.0001)…”

    https://joi.pm-research.com/content/25/3/69

    IE tail ratio seems to be one or the best indicator to correlate IS and OOS of our Algo

    PRT doesn’t give the tail ratio for now. Does someone of you have a PRT Code to calculate it “simply” in a backtest ?

    Thanks a lot

     

    #134257

    So if I understand correctly, you mean by dividing the 95th percentile by the 5th one of the returns distribution you get a significant ratio to predict a good OOS? But if the strategy is over-optimized in IS, what is the purpose?

    #134261

    It’s not indicated in the article @nicolas, but it’s up to us not to overfit to have a better “prediction”

    Do you have an idea to calculate “easily” these 95 and 5 percentile on a backtest (I don’t find an easy method) ?

    #134277

    I love the conclusion (Based on 888 algorithms) :

    “…While the results described above are relevant by themselves, overall, predictability of OOS performance was low (R² < 0.25) suggesting that it is simply not possible to forecast profitability of a trading strategy based on its backtest data…”

    #134332

    The conclusion could also have been written with: despite all the analytical data that we can study, nobody will ever be able to predict the future, not even math!

    Calculate easily: no, but could be possible now with $array.

     

    #134363

    Thanks @Nicolas

    But I’m afraid that even with Array it will take a lot of time

    Do you have a code/snippet to test ?

    Thanks

    #134368

    Even with array, I think we will need a For/Next loop who will be very consuming in time

    #134391

    Yes, that involved nested loops for sure.

    Simple description found on the web, in order to get it clear in mind:

    1. Collect all the data samples.
    2. Sort the data set by value from highest to lowest and discard the highest 5% of the sorted samples.
    3. The next highest sample is the 95th percentile value for the data set.

     

    #134401

    Yes @Nicoals it’s that.

    It’s not all data samples, only the gain of each trade (it will be faster)

    #134427

    This is just a generic term, so data would be anything you like. In this case data would be the positionperf.

Viewing 10 posts - 1 through 10 (of 10 total)

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