Curve fitting in trading: why your backtest lies to you
Curve fitting versus discovery: how iterative tweaking creates false confidence, and how walk-forward and robustness tooling push back.
Curve fitting trading strategy and trading system curve fitting test searches point to the same failure mode: you adjust a model until it hugs historical prices. The backtest looks brilliant because you optimized on the path you judge.
How curve fitting sneaks in
What to do instead
- Fix a research protocol before touching parameters
- Use walk-forward discipline (What is WFA?)
- Treat hyperopt winners as suspects (Hyperopt)
The emotional trap
Curve fitting feels like progress because the chart improves immediately. Real discovery is slower: it shows up as robustness under stress, not as a prettier backtest line.
A simple test
Ask: "If I freeze parameters and roll time forward, does the edge still exist?" If the answer requires more tuning, you are still fitting (What is WFA?).
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