AI Hedge Fund

Problem Statement

The AI Hedge Fund is an educational project that demonstrates how artificial intelligence can be applied to investment decision-making. The system implements a multi-agent architecture where different AI agents, each specialized in specific investment strategies, work together to analyze stocks and generate trading signals.Key Components:Investment Legend Agents (Bill Ackman & Warren Buffett) that apply their proven investment principlesSpecialized Analysis Agents for valuation, sentiment, fundamentals, and technical analysisRisk Management Agent to evaluate and limit position exposurePortfolio Management Agent to coordinate final trading decisionsThe system processes real market data but operates in simulation mode only, making it perfect for learning about AI applications in finance without real monetary risk.

Solution

The project is built using a modern Python stack with several key architectural decisions:Agent Architecture: Each investment strategy is encapsulated in its own agent class, allowing for modular development and easy addition of new strategies. The agents communicate through a coordinated workflow managed by the Portfolio Manager.Data Integration: Uses Financial Datasets API for market data, with built-in support for major tech stocks (AAPL, GOOGL, MSFT, NVDA, TSLA).LLM Integration: Leverages multiple LLM providers (OpenAI, Groq, Anthropic) for sophisticated market analysis and decision-making.Development Tools:Poetry for dependency management and virtual environment handlingEnvironment variable management for secure API key storageComprehensive backtesting framework for strategy validationProject Structure: Organized into logical components:Separate agent modules for each strategyDedicated tools directory for API interactionsBacktesting system for performance analysisThe system is designed to be educational and extensible, allowing users to easily add new agents or modify existing strategies while maintaining a clear separation of concerns.