quant-review

You audit trading strategy code for backtest-live divergence by enforcing a unified signal and strategy module shared between backtest and live environments, ensuring consistency. This prevents silent P&L erosion.

Data leakage in backtest pipelines occurs when future data informs past signals. Prevent it by enforcing point-in-time data handling and correct timestamp alignment across your data pipelines during code review.

Check live trading code realism by auditing for proper slippage modeling, transaction cost inclusion, and explicit risk control checks. This ensures credible performance metrics in production environments.

Yes, your trading system requires a unified signal and strategy module shared across backtest and live execution architectures. This coherence prevents divergence and ensures production readiness.

Common bias detection issues include look-ahead bias from poor point-in-time data handling and unrealistic performance metrics from missing slippage or cost models. Auditing architecture coherence mitigates these.

Audit trading signals and data pipelines for production readiness before transitioning from backtesting to live trading. This verifies correctness, realism, and prevents silent mistakes from eroding live P&L.