TradingAgents: Multi-Agents LLM Financial Trading Framework

Yijia Xiao, Edward Sun, Di Luo and others propose TradingAgents, a stock trading framework inspired by trading firms, in which LLM-driven agents play specialized roles such as fundamental analysts, sentiment analysts, technical analysts, and traders with different risk preferences. According to the paper, the framework also includes bullish and bearish researchers to assess market conditions, a risk management team to monitor exposure, and traders who make decisions by synthesizing debates and historical data. The authors say that the detailed architecture and extensive experiments show that the framework outperforms baseline models in cumulative return, Sharpe ratio, and maximum drawdown, highlighting the potential of multi-agent LLM frameworks in financial trading. The code has been released on GitHub.