AI Hedge Fund

1 week ago 10

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.

This system employs several agents working together:

Aswath Damodaran Agent - The Dean of Valuation, focuses on story, numbers, and disciplined valuation
Ben Graham Agent - The godfather of value investing, only buys hidden gems with a margin of safety
Bill Ackman Agent - An activist investor, takes bold positions and pushes for change
Cathie Wood Agent - The queen of growth investing, believes in the power of innovation and disruption
Charlie Munger Agent - Warren Buffett's partner, only buys wonderful businesses at fair prices
Michael Burry Agent - The Big Short contrarian who hunts for deep value
Peter Lynch Agent - Practical investor who seeks "ten-baggers" in everyday businesses
Phil Fisher Agent - Meticulous growth investor who uses deep "scuttlebutt" research
Stanley Druckenmiller Agent - Macro legend who hunts for asymmetric opportunities with growth potential
Warren Buffett Agent - The oracle of Omaha, seeks wonderful companies at a fair price
Valuation Agent - Calculates the intrinsic value of a stock and generates trading signals
Sentiment Agent - Analyzes market sentiment and generates trading signals
Fundamentals Agent - Analyzes fundamental data and generates trading signals
Technicals Agent - Analyzes technical indicators and generates trading signals
Risk Manager - Calculates risk metrics and sets position limits
Portfolio Manager - Makes final trading decisions and generates orders

Note: the system simulates trading decisions, it does not actually trade.

This project is for educational and research purposes only.

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

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

Setup
- Using Poetry
- Using Docker
Usage
- Running the Hedge Fund
- Running the Backtester
Project Structure
Contributing
Feature Requests
License

Clone the repository:

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

Install Poetry (if not already installed):

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

Install dependencies:

Set up your environment variables:

# Create .env file for your API keys cp .env.example .env

Set your API keys:

# For running LLMs hosted by openai (gpt-4o, gpt-4o-mini, etc.) # Get your OpenAI API key from https://platform.openai.com/ OPENAI_API_KEY=your-openai-api-key # For running LLMs hosted by groq (deepseek, llama3, etc.) # Get your Groq API key from https://groq.com/ GROQ_API_KEY=your-groq-api-key # For getting financial data to power the hedge fund # Get your Financial Datasets API key from https://financialdatasets.ai/ FINANCIAL_DATASETS_API_KEY=your-financial-datasets-api-key

Make sure you have Docker installed on your system. If not, you can download it from Docker's official website.
Clone the repository:

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

Set up your environment variables:

# Create .env file for your API keys cp .env.example .env

Edit the .env file to add your API keys as described above.
Build the Docker image:

# On Linux/Mac: ./run.sh build # On Windows: run.bat build

Important: You must set OPENAI_API_KEY, GROQ_API_KEY, ANTHROPIC_API_KEY, or DEEPSEEK_API_KEY for the hedge fund to work. If you want to use LLMs from all providers, you will need to set all API keys.

Financial data for AAPL, GOOGL, MSFT, NVDA, and TSLA is free and does not require an API key.

For any other ticker, you will need to set the FINANCIAL_DATASETS_API_KEY in the .env file.

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

# On Linux/Mac: ./run.sh --ticker AAPL,MSFT,NVDA main # On Windows: run.bat --ticker AAPL,MSFT,NVDA main

Example Output:

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

# With Poetry: poetry run python src/main.py --ticker AAPL,MSFT,NVDA --ollama # With Docker (on Linux/Mac): ./run.sh --ticker AAPL,MSFT,NVDA --ollama main # With Docker (on Windows): run.bat --ticker AAPL,MSFT,NVDA --ollama main

You can also specify a --show-reasoning flag to print the reasoning of each agent to the console.

# With Poetry: poetry run python src/main.py --ticker AAPL,MSFT,NVDA --show-reasoning # With Docker (on Linux/Mac): ./run.sh --ticker AAPL,MSFT,NVDA --show-reasoning main # With Docker (on Windows): run.bat --ticker AAPL,MSFT,NVDA --show-reasoning main

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

# With Poetry: poetry run python src/main.py --ticker AAPL,MSFT,NVDA --start-date 2024-01-01 --end-date 2024-03-01 # With Docker (on Linux/Mac): ./run.sh --ticker AAPL,MSFT,NVDA --start-date 2024-01-01 --end-date 2024-03-01 main # With Docker (on Windows): run.bat --ticker AAPL,MSFT,NVDA --start-date 2024-01-01 --end-date 2024-03-01 main

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

# On Linux/Mac: ./run.sh --ticker AAPL,MSFT,NVDA backtest # On Windows: run.bat --ticker AAPL,MSFT,NVDA backtest

Example Output:

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

# With Poetry: poetry run python src/backtester.py --ticker AAPL,MSFT,NVDA --start-date 2024-01-01 --end-date 2024-03-01 # With Docker (on Linux/Mac): ./run.sh --ticker AAPL,MSFT,NVDA --start-date 2024-01-01 --end-date 2024-03-01 backtest # With Docker (on Windows): run.bat --ticker AAPL,MSFT,NVDA --start-date 2024-01-01 --end-date 2024-03-01 backtest

You can also specify a --ollama flag to run the backtester using local LLMs.

# With Poetry: poetry run python src/backtester.py --ticker AAPL,MSFT,NVDA --ollama # With Docker (on Linux/Mac): ./run.sh --ticker AAPL,MSFT,NVDA --ollama backtest # With Docker (on Windows): run.bat --ticker AAPL,MSFT,NVDA --ollama backtest

ai-hedge-fund/ ├── src/ │ ├── agents/ # Agent definitions and workflow │ │ ├── bill_ackman.py # Bill Ackman agent │ │ ├── fundamentals.py # Fundamental analysis agent │ │ ├── portfolio_manager.py # Portfolio management agent │ │ ├── risk_manager.py # Risk management agent │ │ ├── sentiment.py # Sentiment analysis agent │ │ ├── technicals.py # Technical analysis agent │ │ ├── valuation.py # Valuation analysis agent │ │ ├── ... # Other agents │ │ ├── warren_buffett.py # Warren Buffett agent │ │ ├── aswath_damodaran.py # Aswath Damodaran agent │ │ ├── ... # Other agents │ │ ├── ... # Other agents │ ├── tools/ # Agent tools │ │ ├── api.py # API tools │ ├── backtester.py # Backtesting tools │ ├── main.py # Main entry point ├── pyproject.toml ├── ...