Tool Open source
QuantsPlaybook is a GitHub resource containing Python reproductions of quantitative-investment research reports from Chinese securities firms. It covers market-timing strategies, factor construction, quantitative value methods, and portfolio optimization, with more than 100 listed strategy implementations including RSRS and QRS timing, volatility and technical-analysis methods, multi-factor models, FFScore, cash-flow selection, differential-evolution portfolio optimization, and deep multi-task time-series momentum. The repository organizes each strategy with related research papers or brokerage reports and Python files containing notebook-based reproductions; its workflows cover data acquisition, analysis, backtesting, visualization, and, where used, machine-learning or signal-decomposition methods. It depends on data sources such as JQData and Tushare and references tools including pandas, NumPy, Qlib, Backtrader, PyTorch, TensorFlow, LightGBM, XGBoost, scikit-learn, and Jupyter.