AINeutralarXiv – CS AI · Apr 146/10
🧠
When Valid Signals Fail: Regime Boundaries Between LLM Features and RL Trading Policies
Researchers demonstrate that large language models can extract predictive features from financial news with valid intermediate signals (Information Coefficient >0.15), yet these features fail to improve reinforcement learning trading agents during macroeconomic shocks. The findings reveal a critical gap between feature-level validity and downstream policy robustness, suggesting that valid signals alone cannot guarantee trading performance under distribution shifts.
