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Forums>StrategyQuant>General Discussion>Genetic evolution: Should you recycle strategies as an input population?

  • #257423 |
    Customer
    29 Posts

    Hi all. Once you’ve run a workflow end to end then you’ve built up a set of failed strategies at each stage of the workflow (and hopefully some successful ones at the very end!). Would it be a good idea to collect up a decent number of the later workflow strategies and use them as a genetic evolution input population for the next workflow? Would this perhaps result in too many strategies that are correlated with one another?

    #257431
    Oliver
    Customer
    117 Posts

    Ive had some success where ive generated some strategies which have not necessary passed all robustness tests. I have then gone back to run the initial OOS test.  Those that pass, i then loaded into the initial population tab and found strategies which then go on to pass all robustness tests.

    #257440
    Customer
    29 Posts

    Thanks Oliver. The next stage after Builder in my workflow is to test with additional precision. I found that loading up 400 of the strategies that make it through this first step into the Initial Population increased the Builder speed from 85 to over 600 strategies per hour (and that’s even with an additional stability measure added!). There seems to be about the same level of attrition as I put them through the robustness checks. Haven’t built up enough of a sample to say whether they are highly correlated…

    #257455
    Oliver
    Customer
    117 Posts

    Yes it does produce a lot of correlated strategies but i find that if you batch process them you can find some really good ones which which pass all the robustness tests and even work better on other markets.

    #257459
    Customer
    29 Posts

    Ok cool. Thanks!

    #260522
    Customer
    109 Posts

    I have then gone back to run the initial OOS test.

    Hi,

    I’m new to strategy quant and also looking at how best to recycle strategies.

    What do you mean by this statement above? Do you mean that you take the failed strategies and then train them on the OOS data (ie: you use the OOS as IS)?

     

    #260555
    Oliver
    Customer
    117 Posts

    so i build using most signals, indicators and price entries using random generation. i then back test those on earlier years. if they meet certain metrics i then keep them and use in the recycling process. the random build process takes a while. i do this because want un corellated strategies. this is the best way i have found to do it without spending too much time

    #260607
    Insanity82007
    Customer
    28 Posts

    To be honest, you’re better off generating new strategies for 2 reasons:

    1. More variety in your portfolios.

    2. Less overhead. It’s a headache managing large volumes of pre-generated strategies, especially when SQ can generate new strats so fast. I scrapped 200k strats a while ago for this reason and never looked back

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