Tuning a strategy so closely to past data that it stops working on new data. Also called overfitting.
Curve fitting happens when a strategy's settings are adjusted again and again until the backtest looks excellent. The strategy has then learned the noise of that particular period, not a pattern that repeats.
Signs of curve fitting include a very smooth backtest, a large number of adjustable settings, and results that collapse when tested on a period the developer did not use. Ask whether the strategy was tested on data it had never seen.
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