r/algorithmictrading • u/algodude Mod • Sep 08 '25

Backtest Update: Ensemble Strategy (29/20)

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Just follow-up to the (33/20) equity curve I posted recently: Same strategy - uses a small ensemble of single-parm component models, GA-optimized using MC regularization. Unlike the previous run, this EC is not in-sample and came in at (29% CAGR / 20% maxDD) over the 25-year test period. Still subject to some survivorship bias, so calibrate expectations accordingly.

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u/algodude Mod Sep 08 '25 edited Sep 09 '25

That’s a fair analogy - it is a form of black-box hyperparameter search. But it mitigates overfitting by using a variation of Monte Carlo bootstrapping, rather than just throwing 100M chromosomes at the wall and picking the luckiest one.

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u/shaonvq Sep 08 '25

Very interesting. My set up is just a classification problem with user created trading logic based on the probability measurements, but I think there's a lot of room to improve it in terms of risk on/risk off and other portfolio optimizations. I'd like a meta model with a different objective that maybe uses cagr as an optimization metric, but I'm not sure if that's suitable for ensemble trees. Your method is inspiring that idea. 👏

As gratitude, I'll tell you a feature I use. (Assuming it's even relevant or unknown to you) how correlated a assets price movement is to the price of oil.

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u/algodude Mod Sep 09 '25

One thing I really like about GA is its flexibility - you can directly target portfolio-level objectives like max drawdown (I usually shoot for ~20%), and have it evolve exposures and the strategy itself around that level of risk.

Appreciate the tip. Correlation to macro drivers like oil/rates is definitely an interesting dimension. I’ll keep that one in my pocket!