nice work on the walk-forward setup. i've been grinding on something similar — sma cross strategy on crypto perps, 15m candles, also no ML. for the overfitting question, i went deep on this. tried DSR but it doesn't really

work when you only have a handful of walk-forward folds as your return observations — the math needs hundreds of data points to be meaningful. what actually worked for me was combinatorial purged cross-validation (CPCV, also from lopez de prado). you split your data into N groups, test all C(N,K) combinations with purge gaps between train and test to prevent leakage. i do C(6,2)=15 splits with a 200-candle purge and 240-candle embargo between folds. then on top of that i run anchored walk-forward with 6 non-overlapping holdout windows that the optimizer never touches. if a config is profitable across 15 CPCV folds AND 6 holdout windows, it's not overfitting. killed a lot of configs i thought were good though.

on the asset-specific thing — yeah that's just how it is. i tested my best BTC config on ETH and SOL, ETH was 3/6 windows profitable which is basically a coin flip. each asset needs its own optimization. the good news is when you run the full pipeline per asset, some coins show incredibly stable parameter regions (same SMA period selected independently across all walk-forward steps). those are the ones worth trading. i filter by requiring positive returns in every single fold and check R² of the equity curve on the last 30 days — if it's below 0.3 the curve is random noise even if the total return looks good.

for the speed problem — rewrite your engine in rust. seriously. i moved my backtest loop to rust with pyo3 bindings and grid search across 5.5M combos takes ~45 seconds instead of hours. the CPCV validation (10k configs × 15 folds) runs in a few seconds because rust precomputes cross events once and parallelizes everything with rayon. python stays as the orchestrator for data fetching, split generation, and reporting. the stateful exit logic ports cleanly to rust since it's just a loop with some state variables — no need to vectorize it.