Backtesting Analysis

Overfitting detection identifies when a strategy performs well on historical data but may fail live. Check red flags: Sharpe ratio above 3.0, win rate exceeding 75%, or fewer than 20 total trades. These suggest curve-fitting to past price action rather than robust strategy logic.

Key backtest metrics include Sharpe ratio for risk-adjusted returns, maximum drawdown for peak loss, win rate for trade success frequency, and profit factor for revenue relative to losses. Together they reveal strategy reliability across different market regimes and stress scenarios.

A backtest becomes actionable when it avoids overfitting red flags and demonstrates consistent metrics across regime types—momentum, mean reversion, trend following, and breakout. Sufficient trade count, moderate Sharpe, and acceptable drawdown suggest the strategy captures real market behavior, not noise.

Strategy comparison across momentum, mean reversion, trend following, and breakout regimes reveals which approach suits your market environment. Backtesting Analysis evaluates performance per regime and flags strategies that work only in narrow conditions, indicating overfitting or limited applicability.

Low trade count with high Sharpe is a primary overfitting red flag. Few trades mean limited statistical evidence; results may reflect luck rather than repeatable strategy logic. Proceed to live trading only if the strategy performs consistently across multiple regimes and time periods.