Representation Signatures and Risk-Feedback Alignment in LLM Trading Agents

This research investigates the behavioral alignment and representation dynamics of large language model (LLM) agents in financial decision environments. Using TradeArena, measurable pre-failure signatures were found, including planning embeddings drifting and fused plan-risk representations separating before drawdowns, indicating effective-rank contraction.