backtest-validator

You validate backtest metrics by enforcing hard constraints like zero-trade invalidation, metric clamping for Sharpe and Sortino, and net-of-cost checks to detect extreme values and unintended artifacts. This ensures metric integrity across post-backtest analysis.

Extreme Sharpe or Profit Factor values occur when backtest metrics are not clamped within defined ranges. A validation pass flags these suspicious metric values for review to prevent misleading insights during fitness evaluation.

You invalidate zero-trade backtest runs by applying a hard constraint that automatically flags and rejects such outcomes. This prevents misleading insights from entering the fitness evaluation pipeline.

Yes, backtest validation performs end-to-end checks by cross-referencing fitness evaluation and SIMD metric calculations. This ensures net-of-cost accuracy and confirms that metrics are sane and compliant.

The best way to run a sanity check is to execute a validation pass on your latest backtest results. This enforces metric clamping and catches unintended artifacts across your strategies.

You should not rely solely on automated backtest validation when your strategy logic requires custom anomaly detection beyond defined metric clamp ranges, as the validation focuses on standard fitness evaluation constraints like zero-trade invalidation.