TPTBusiness ad206345cc feat: Full auto strategy generation in fin_quant loop ...

Integrated StrategyOrchestrator into QuantRDLoop feedback cycle:
- Replaced old StrategyCoSTEER with new StrategyOrchestrator
- Uses improved prompt (strategy_generation_v2.yaml)
- Forward-fills daily factors to 1-min OHLCV
- Realistic backtesting with real OHLCV data + spread costs
- Optuna hyperparameter optimization (20 trials per strategy)
- Auto-generates 3 strategies every 500 factors

Features:
- IC-guided factor selection (|IC| > 0.10 PRIORITIZE)
- Real price returns from intraday_pv.h5
- 1.5 bps spread cost per trade
- Proper annualization for 1-min data
- Graceful error handling (doesn't break main loop)

Usage:
  rdagent fin_quant --auto-strategies                    # Auto every 500 factors
  rdagent fin_quant --auto-strategies --auto-strategies-threshold 1000  # Every 1000

Or manual:
  rdagent generate_strategies --count 5 --optuna         # 5 strategies with Optuna

Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>

2026-04-09 14:13:08 +02:00

..

conf.py

feat: add a web UI server (#1345)

2026-03-18 14:04:52 +08:00

factor_from_report.py

feat: add a web UI server (#1345)

2026-03-18 14:04:52 +08:00

factor.py

feat: add a web UI server (#1345)

2026-03-18 14:04:52 +08:00

model.py

feat: add a web UI server (#1345)

2026-03-18 14:04:52 +08:00

prompts.yaml

feat: EURUSD Trading-Verbesserungen implementiert (Phase 1)

2026-03-30 19:56:26 +02:00

quant.py

feat: Full auto strategy generation in fin_quant loop

2026-04-09 14:13:08 +02:00