This is a proof of concept for an AI-powered hedge fund. The goal of this project is to explore the use of AI to make trading decisions. This project is for educational purposes only and is not intended for real trading or investment.

🚧 The project is evolving. We're rebuilding it into a persistent, always-on AI hedge fund — a fund as a first-class entity you can backtest, paper-trade, and (opt-in) run live, with the investor agents reimagined as pluggable, backtestable "alpha models." Read the Vision → and the Roadmap →.

This system employs several agents working together:

1. Aswath Damodaran Agent - The Dean of Valuation, focuses on story, numbers, and disciplined valuation
2. Ben Graham Agent - The godfather of value investing, only buys hidden gems with a margin of safety
3. Bill Ackman Agent - An activist investor, takes bold positions and pushes for change
4. Cathie Wood Agent - The queen of growth investing, believes in the power of innovation and disruption
5. Charlie Munger Agent - Warren Buffett's partner, only buys wonderful businesses at fair prices
6. Michael Burry Agent - The Big Short contrarian who hunts for deep value
7. Mohnish Pabrai Agent - The Dhandho investor, who looks for doubles at low risk
8. Nassim Taleb Agent - The Black Swan risk analyst, focuses on tail risk, antifragility, and asymmetric payoffs
9. Peter Lynch Agent - Practical investor who seeks "ten-baggers" in everyday businesses
10. Phil Fisher Agent - Meticulous growth investor who uses deep "scuttlebutt" research
11. Rakesh Jhunjhunwala Agent - The Big Bull of India
12. Stanley Druckenmiller Agent - Macro legend who hunts for asymmetric opportunities with growth potential
13. Warren Buffett Agent - The oracle of Omaha, seeks wonderful companies at a fair price
14. Valuation Agent - Calculates the intrinsic value of a stock and generates trading signals
15. Sentiment Agent - Analyzes market sentiment and generates trading signals
16. Fundamentals Agent - Analyzes fundamental data and generates trading signals
17. Technicals Agent - Analyzes technical indicators and generates trading signals
18. Risk Manager - Calculates risk metrics and sets position limits
19. Portfolio Manager - Makes final trading decisions and generates orders

Note: the system does not actually make any trades.

This project is for educational and research purposes only.

• Not intended for real trading or investment
• No investment advice or guarantees provided
• Creator assumes no liability for financial losses
• Consult a financial advisor for investment decisions
• Past performance does not indicate future results

By using this software, you agree to use it solely for learning purposes.

• How to Install
• How to Run
  • ⌨️ Command Line Interface
  • 🖥️ Web Application
• How to Contribute
• Feature Requests
• License

Before you can run the AI Hedge Fund, you'll need to install it and set up your API keys. These steps are common to both the full-stack web application and command line interface.

git clone https://github.com/virattt/ai-hedge-fund.git
cd ai-hedge-fund

Create a .env file for your API keys:

# Create .env file for your API keys (in the root directory)
cp .env.example .env

Open and edit the .env file to add your API keys:

# For running LLMs hosted by openai (gpt-4o, gpt-4o-mini, etc.)
OPENAI_API_KEY=your-openai-api-key

# For getting financial data to power the hedge fund
FINANCIAL_DATASETS_API_KEY=your-financial-datasets-api-key

Important: You must set at least one LLM API key (e.g. OPENAI_API_KEY, GROQ_API_KEY, ANTHROPIC_API_KEY, or DEEPSEEK_API_KEY) for the hedge fund to work.

You can run the AI Hedge Fund directly via terminal. This approach offers more granular control and is useful for automation, scripting, and integration purposes.

1. Install Poetry (if not already installed):

curl -sSL https://install.python-poetry.org | python3 -

2. Install dependencies:

poetry install

poetry run python src/main.py --ticker AAPL,MSFT,NVDA

You can also specify a --ollama flag to run the AI hedge fund using local LLMs.

poetry run python src/main.py --ticker AAPL,MSFT,NVDA --ollama

You can optionally specify the start and end dates to make decisions over a specific time period.

poetry run python src/main.py --ticker AAPL,MSFT,NVDA --start-date 2024-01-01 --end-date 2024-03-01

poetry run python src/backtester.py --ticker AAPL,MSFT,NVDA

Example Output:

Note: The --ollama, --start-date, and --end-date flags work for the backtester, as well!

The new way to run the AI Hedge Fund is through our web application that provides a user-friendly interface. This is recommended for users who prefer visual interfaces over command line tools.

Please see detailed instructions on how to install and run the web application here.

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

Important: Please keep your pull requests small and focused. This will make it easier to review and merge.

If you have a feature request, please open an issue and make sure it is tagged with enhancement.

This project is licensed under the MIT License - see the LICENSE file for details.