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Step 3 - LLM Prompt verbessert: - Created prompts/strategy_generation_v2.yaml - IC-guided factor selection instructions - |IC| > 0.10: PRIORITIZE, |IC| > 0.05: USE, |IC| < 0.05: AVOID - IC-weighted factor combinations - Better examples with IC weights - Added 'close' Series to available scope Step 5 - Optuna-Optimierung aktiviert: - Added use_optuna=True, optuna_trials=20 to __init__ - Integrated OptunaOptimizer in _generate_and_evaluate_single - Added _prepare_factor_values method for Optuna - Auto-optimizes accepted strategies with 20 trials - Updates results if Optuna improves Sharpe Test results (MomentumDivergenceZScore with forward-fill): - Status: accepted - Sharpe: 6.04 - Max DD: -1.57% - Win Rate: 49.19% - Ann Return: 21.88% - Periods: 823,450 (2.27 years) Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>