Overfitting
Tuning a strategy until it fits the historical data's noise rather than a real market pattern. Symptoms: many parameters, spectacular backtest, sharp sensitivity to small parameter changes, and disappointing live results. Defenses: fewer knobs, out-of-sample testing, walk-forward validation, and suspicion of your own best results.
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Related terms
Out-of-Sample TestingEvaluating a strategy on data it was not developed or tuned on — the l…Walk-Forward AnalysisRepeatedly optimizing a strategy on one window of history and testing …BacktestingSimulating a strategy's rules against historical market data to estima…
Backtests are hypothetical, computed by DeployQuant's engine on minute-resolution consolidated US market data (2021-01-04 to 2026-07-17, $10,000 starting capital, no margin, fees and slippage not modeled) and do not guarantee future results. Nothing on this page is investment advice. Live trading involves risk of loss.