backtest-diagnose

To fix a quantitative trading backtest returning zero trades or NaN values, you must systematically inspect metrics, equity curves, and signal engine source code to pinpoint whether it is a runtime error, logic bug, or data-source issue, then apply iterative code modifications to restore performance.

The best way to debug algorithmic trading backtest failures is through automated error classification that categorizes the failure as a runtime error, logic bug, or data-source issue, followed by targeted diagnostic inspection of signal logic and iterative validation.

Yes, you can diagnose underperforming backtests using local source code files because the diagnostic workflow requires access to local artifacts and source code files to perform iterative validation and apply the necessary code modifications to your signal engine.

Your algorithmic trading backtest may fail during runtime execution due to logic bugs, data-source issues, or runtime errors within your signal engine code, which require systematic inspection of equity curves and metrics to properly diagnose and repair.

Yes, you need to provide your signal engine code to repair an underperforming trading backtest, as the diagnostic workflow requires access to local artifacts and source code files to analyze the failure and apply the necessary iterative code fixes.