Modular Quantitative Trading Backtesting Framework

Published: January 05, 2025

Timeline: Sep. 2024 – Jan. 2025
Advisor: Prof. Changhao Jiang, Peking University

This course project focused on building a professional-grade backtesting engine from scratch.

Architecture: Engineered a modular, object-oriented framework in Python, decoupling signal generation from order execution to support highly customizable trading algorithms.
Strategies: Designed and implemented diverse quantitative strategies, including Momentum, Mean Reversion (Bollinger Bands), Cross-Sectional, and Time-Series, utilizing pandas and NumPy for vectorized processing.
Analytics: Developed an analytics module to compute key performance indicators (e.g., Sharpe Ratio, Annualized Returns) and automated the generation of visual performance reports.