Open Source AI Hedge Fund: A Team of Agents That Trade Together

There is an open source project called AI Hedge Fund that uses multiple AI agents, each modeled after a different investing philosophy, to collaborate on portfolio decisions. The agents work together, pass signals through a risk manager, and ultimately let a portfolio manager make the final call on whether to buy, sell, short, cover, or hold.

How It Works

The project assembles a team of AI agents, each named after a famous investor or analytical approach. The roster includes:

• Ben Graham Agent (value investing fundamentals)
• Warren Buffett Agent (long-term quality holdings)
• Charlie Munger Agent (mental models and contrarian thinking)
• Bill Ackman Agent (activist-style analysis)
• Cathie Wood Agent (growth and innovation focus)
• Sentiment Agent (market sentiment analysis)
• Technicals Agent (technical chart analysis)
• Valuation Agent (quantitative valuation models)

Each agent produces trading signals independently based on its own methodology.

The Decision Pipeline

The agents do not trade independently. Their signals flow through two management layers:

1. Risk Manager: Aggregates signals from all agents and evaluates overall portfolio risk.
2. Portfolio Manager: Takes the risk-adjusted signals and makes a final trading decision.

The portfolio manager chooses from five actions: buy, cover, sell, short, or hold. This layered structure prevents any single agent's bias from dominating the portfolio.

Key Takeaways

• The AI Hedge Fund is open source, meaning you can set it up, inspect the code, and modify the agents yourself.
• Each agent applies a distinct investing philosophy, from Buffett-style value investing to Cathie Wood-style growth plays.
• A risk manager and portfolio manager sit on top of the agent team to prevent any single strategy from running unchecked.

Resources

• AI Hedge Fund (GitHub) -- Open source multi-agent trading system