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TRADINGAGENTS

Multi-Agent LLM Financial Trading Framework

Apache-2.0

ABOUT

Financial trading requires synthesizing diverse signals from fundamentals, market sentiment, technical indicators, macroeconomic news, and risk metrics — then making coordinated decisions under uncertainty. Traditional algorithmic trading systems struggle to incorporate qualitative analysis and multi-perspective debate. TradingAgents solves this by deploying specialized LLM-powered agents that mirror a real trading firm's hierarchy, collaborating through structured debates to evaluate risks, balance bullish and bearish perspectives, and determine optimal trading strategies.

INSTALL
pip install tradingagents

INTEGRATION GUIDE

1. Deploy multi-agent trading teams that collaboratively evaluate market conditions and make informed decisions 2. Synthesize fundamental analysis, technical indicators, and sentiment signals into coordinated trading strategies 3. Backtest LLM-driven trading strategies across historical market data with configurable risk parameters 4. Research multi-agent debate architectures for financial decision-making under uncertainty 5. Integrate with multiple LLM providers (OpenAI, Gemini, Claude, Grok, DeepSeek, Qwen) for diversified agent reasoning

TAGS

agentsfinancetradingllmmulti-agentpythonresearch