Python Backtesting Framework Audit Report

這項服務交付什麼

I perform a rigorous, evidence-based audit of your Python backtesting framework to detect critical flaws that could invalidate live trading results. Using my open-source validator and proprietary methodology, I test for look-ahead bias (via execution-time perturbation), overfitting (via effective sample size analysis), and unreproducibility (via SHA256 hash verification across environments). You receive a concise, technical PASS/FAIL report with clear root-cause explanations, reproducible steps, and actionable remediation guidance — all delivered asynchronously via secure digital channel. No black-box scoring: every finding is traceable to code, data, or configuration.

你需要提供

Your backtesting Python codebase (repository or archive), full environment specification (Python version, key package versions like pandas, NumPy, backtrader/zipline/vnpy), and historical market data used in the test run. Note: Covers up to 3,000 lines of code (LOC). Contact me for a custom quote if your project is larger.

Python

LB

look-ahead bias auditing

RA

reproducibility audit