# AI Hedge Fund — Multi-Agent LLM Trading Research Framework

> A multi-agent system that simulates a team of financial analysts using LLMs. Agents perform fundamental analysis, technical analysis, sentiment analysis, and risk management to generate trading signals.

## Install

Save in your project root:

# AI Hedge Fund — Multi-Agent LLM Trading Research Framework

## Quick Use
```bash
git clone https://github.com/virattt/ai-hedge-fund.git
cd ai-hedge-fund
cp .env.example .env
# Add your OpenAI API key and Financial Datasets API key to .env
pip install -r requirements.txt
python src/main.py --ticker AAPL --show-reasoning
```

## Introduction
AI Hedge Fund is an open-source project that demonstrates how multiple AI agents can collaborate to analyze stocks the way a real hedge fund research team would. It is designed as an educational and experimental framework, not a production trading system.

## What AI Hedge Fund Does
- Runs a team of specialized AI agents that each perform a distinct role in stock analysis
- Simulates fundamental analysis by examining financial statements, ratios, and intrinsic value models
- Performs technical analysis using price action, moving averages, and momentum indicators
- Conducts sentiment analysis by processing recent news and market commentary
- Combines all agent outputs through a risk manager agent that produces a final buy/hold/sell signal with reasoning

## Architecture Overview
The system uses a multi-agent orchestration pattern where each agent is an LLM with a specialized system prompt and access to financial data tools. A portfolio manager agent delegates research tasks to sub-agents (fundamentals, technicals, sentiment, valuation), each of which queries financial APIs, processes the data, and returns structured analysis. The risk manager then synthesizes all perspectives, weighs conflicting signals, and outputs a final recommendation with a confidence score. The entire pipeline runs as a sequential workflow coordinated through Python.

## Self-Hosting & Configuration
- Clone the repository and install Python dependencies via pip
- Provide an OpenAI API key in the `.env` file for LLM inference
- Provide a Financial Datasets API key for accessing stock market data
- Configure which ticker symbols to analyze via command-line arguments
- Optionally adjust agent prompts in the source to customize analysis style or add new agents

## Key Features
- Transparent reasoning: each agent shows its full chain of thought before the final signal
- Modular agent design makes it straightforward to add or remove analyst roles
- Supports backtesting mode to evaluate signal quality against historical data
- Works with any ticker available through the Financial Datasets API
- Clean Python codebase that serves as a reference implementation for multi-agent financial applications

## Comparison with Similar Tools
- **FinGPT** — focuses on fine-tuning LLMs on financial data; AI Hedge Fund uses prompt-based agents with no fine-tuning
- **AutoGen (Microsoft)** — general-purpose multi-agent framework; AI Hedge Fund is purpose-built for financial research with domain-specific agents
- **CrewAI** — generic agent orchestration; AI Hedge Fund provides pre-built financial analyst roles and data integrations out of the box
- **OpenBB** — terminal and SDK for financial data access; AI Hedge Fund adds an LLM reasoning layer on top of data retrieval
- **QuantConnect / Zipline** — algorithmic trading platforms with backtesting; AI Hedge Fund emphasizes LLM-driven qualitative analysis rather than quantitative strategies

## FAQ
**Q: Can I use this for real trading?**
A: The project is explicitly educational. The authors warn against using it for actual trading decisions without extensive validation and risk controls.

**Q: Which LLM providers are supported?**
A: The default setup uses OpenAI models. The codebase can be adapted to use other providers by modifying the LLM client configuration.

**Q: How does it get financial data?**
A: It uses the Financial Datasets API to pull income statements, balance sheets, price history, and news. You need a valid API key.

**Q: Can I add my own analysis agents?**
A: Yes. Each agent is a self-contained Python module with a system prompt and tool definitions. You can create new agents by following the existing pattern.

## Sources
- https://github.com/virattt/ai-hedge-fund
- https://github.com/virattt/ai-hedge-fund/blob/main/README.md

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Source: https://tokrepo.com/en/workflows/asset-aaa9ce84
Author: AI Open Source