This category focuses on the end-to-end process of designing, backtesting, and evaluating an ML-driven trading strategy introduced in the chapter The ML4T Workflow: From Model to Strategy Backtesting and used throughout the book. Most importantly, it focuses on discussions of how to prepare, design, run and evaluate a backtest using the Python libraries backtrader and Zipline. Relevant topics include:
- Plan and implementing end-to-end strategy backtesting
- Avoiding critical pitfalls when implementing backtests
- Using Zipline and backtrader to design and evaluate your own strategies