Can LLMs improve financial trading robustness?
HedgeAgents: A Balanced-aware Multi-agent Financial Trading System
HedgeAgents, a multi-agent system using LLMs, aims to improve the robustness of automated financial trading by incorporating hedging strategies. A central fund manager agent coordinates three specialist trading agents (stocks, Bitcoin, Forex) through different types of “conferences” (budget allocation, experience sharing, and extreme market response). Each agent leverages LLMs, tools, and memories to make decisions. Key LLM aspects include prompt engineering for decision-making, memory retrieval for experience replay, and generating intelligent investment summaries. The system outperformed baselines on various metrics, demonstrating the potential of LLM-driven multi-agent collaboration for financial trading.