Overfitting

Tuning a strategy so tightly to past data that it fails on new data.

Overfitting is fitting the noise instead of the signal: the curve looks perfect in-sample and falls apart live. Out-of-sample testing, walk-forward analysis, and a deflated Sharpe are the standard defenses — and the reason a beautiful equity curve is never enough on its own.