backtest-guard

To detect look-ahead bias and data leakage in backtest code, you can submit your strategy scripts to an automated audit that enforces point-in-time checks and outputs a severity-ranked integrity report with precise file and line references.

Data snooping and overfitting in quantitative backtesting occur when parameter sweeps or signal generation fit historical noise rather than genuine market signals. An automated pitfall encyclopedia can audit your code to expose these execution realism flaws and rank their severity.

You audit execution realism and transaction cost assumptions by running your strategy code through an automated review that checks成交真实性 against 48 specific rules, generating a structured health check report with actionable risk control points.

Yes, you can audit backtest integrity without external data. The review enforces deterministic evaluation and traceability by analyzing your code logic for suspicious patterns directly, requiring no external market data feeds to generate the severity-ranked report.

To fix return calculation errors in a trading backtest, run your code through an automated audit that identifies收益口径错误 (return caliber mistakes) and provides executable repair directions without subjective assumptions.

Yes, overfitting detection works on data loading and signal generation scripts. The audit covers the entire workflow including parameter optimization, applying point-in-time checks to expose data-snooping traps across all processing stages.