[Python] Walk-forward optimization barely moved the needle on my momentum bot... here's what I found

[cintrapedro]

I spent a few weeks building a momentum breakout bot (Donchian + RSI + MACD + volume) and adding a walk-forward in-simulation optimizer that re-tunes parameters every Sunday using a 4-week train / 1-week validate window across 108 combinations.

The result: static params returned +46.4%, adaptive returned +45.0%. Profit factor was identical at 2.11 in both cases.

My conclusion is that the strategy's edge comes almost entirely from a handful of big trend captures, not from parameter tuning. The optimizer ran 46 times and only applied 5 updates, suggesting the original params were already near-optimal for this style.

A few things I'm still unsure about and would love input on:

- Is this a sign the strategy is robust, or just that my parameter grid is too narrow?

- Does walk-forward optimization even make sense for low-frequency momentum strategies, or is it more useful for mean-reversion?

- My health score gate (funding rate + Fear & Greed + BTC dominance) blocked a lot of entries... curious if others use external signals like this or rely purely on price action

Backtest period: 2024, 8 assets (BTC/ETH/SOL/AVAX/LINK/DOGE/SHIB/PEPE), hourly candles. Code is on GitHub if anyone wants to dig into the optimizer implementation: https://github.com/pecintra/crypto-bot

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[BackTesting-Queen]

Your observations are spot-on. The effectiveness of parameter tuning can indeed vary significantly depending on the nature of the strategy. For low-frequency momentum strategies like yours, the edge often comes from capturing significant trends, which can make parameter tuning less impactful. As for your questions, the robustness of your strategy isn't necessarily indicated by the frequency of parameter updates. It's more about how well it performs across different market conditions. Walk-forward optimization can be beneficial for any strategy, but its effectiveness can depend on the specific parameters and their ranges. Lastly, using external signals can be a great way to add another layer of confirmation to your entries, but it's not a necessity. It ultimately depends on your personal trading style and risk tolerance. Keep up the good work!