Chapter 11: Parameter Optimization and Robustness Validation

This chapter is currently maintained in Chinese first.

• Chinese chapter: 第 11 章：参数优化与稳健性检验
• Textbook home: Chinese textbook index
• Practice links:
• Primary example: examples/textbook/ch11_optimization.py
• Extended example: examples/02_parameter_optimization.py
• Guide: Optimization Guide

Key optimization parameters (new):

• forward_worker_logs in run_grid_search:
• False (default): better throughput; worker self.log() may not be visible in main process output.
• True: forwards worker logs to the main process for debugging and teaching.
• strict_strategy_params in run_backtest (default True):
• enforces strict constructor parameter validation;
• fails fast on unknown strategy parameters to avoid silent fallback and misleading optimization results.
• run_walk_forward accepts these options via **kwargs passthrough:
• forward_worker_logs applies to in-sample optimization (run_grid_search);
• strict_strategy_params stays effective in both optimization and OOS validation.

WFO passthrough example:

wfo_results = run_walk_forward(
    strategy=TailTradingStrategy,
    param_grid=param_grid,
    data=all_data,
    train_period=250,
    test_period=60,
    max_workers=4,
    forward_worker_logs=True,
    strict_strategy_params=True,
)

Windows note for parallel optimization (max_workers > 1):

• Define strategy classes in an importable module, not in __main__.
• Guard script entry with if __name__ == "__main__":.
• This is caused by Windows multiprocessing spawn, not by fill-policy semantics.