AutoHedge
Autonomous agent hedge fund application — automates market analysis, risk management, and trade execution on Solana
AutoHedge is an autonomous agent hedge fund designed for institutional reliability, automating market analysis, risk management, and trade execution. It uses a multi-agent architecture with specialized agents for strategy, quant analysis, risk, and execution. The system provides structured outputs, comprehensive logging, and supports full autonomous trading on Solana.
- Multi-agent architecture for strategy, quant, risk, and execution
- Integrates with live market data for real-time analysis and execution
- Built-in risk management and position sizing before trade execution
- Generates JSON-formatted recommendations and analysis outputs
- Detailed, configurable logging for audit and debugging
README
View on GitHub ↗AutoHedge
AutoHedge is an enterprise-grade autonomous agent hedge fund that trades on your behalf. It combines swarm intelligence and specialized AI agents to perform end-to-end market analysis, risk management, and execution with minimal human intervention.
Current support: Full autonomous trading on Solana. Coming soon: Coinbase and additional exchanges.
Overview
AutoHedge is built to be the world's most powerful autonomous agent hedge fund. It runs continuous analysis, generates and validates trading theses, sizes risk, and executes orders across supported venues. The system is designed for institutional reliability: structured outputs, comprehensive logging, and a risk-first architecture that scales from single strategies to multi-venue, multi-asset deployment.
Features
Multi-Agent Architecture: Specialized agents for each stage of the trading pipeline
- Director Agent: strategy and thesis generation
- Quant Agent: technical and statistical analysis
- Risk Management Agent: position sizing and risk assessment
- Execution Agent: order generation and execution
Real-Time Market Analysis: Integration with live market data for analysis and execution
Risk-First Design: Built-in risk management and position sizing before any execution
Structured Output: JSON-formatted recommendations and analysis for downstream systems
Enterprise Logging: Detailed, configurable logging for audit and debugging
Extensible Framework: Modular design for custom strategies and new venues
Supported Venues
| Venue | Status | Notes |
|---|---|---|
| Solana | Supported | Full autonomous trading |
| Coinbase | Coming soon | In development |
| Other CEX | Roadmap | Planned expansion |
Quick Start
Installation
pip install -U autohedge
Environment Variables
# Jupiter API (token price & search tools)
# Get a key at https://portal.jup.ag
JUPITER_API_KEY=
# OpenAI (experimental agents)
OPENAI_API_KEY=
ANTHROPIC_API_KEY=
WORKSPACE_DIR="agent_workspace"
# Trading
WALLET_PRIVATE_KEY=""
See .env.example for a full reference.
Basic Usage
autohedge
Architecture
AutoHedge uses a multi-agent pipeline where each agent has a defined responsibility:
graph TD
A[Director Agent] --> B[Quant Agent]
B --> C[Risk Manager]
C --> D[Execution Agent]
D --> E[Trade Output]
Contributing
Contributions are welcome. See Contributing Guidelines for details.
- Fork the repository
- Create a feature branch (
git checkout -b feature/AmazingFeature) - Commit changes (
git commit -m 'Add some AmazingFeature') - Push to the branch (
git push origin feature/AmazingFeature) - Open a Pull Request
License
MIT License. See LICENSE for details.
Acknowledgments
- Swarms for the AI agent framework
Support
- Issue Tracker: GitHub Issues
- Community: Discord
AutoHedge by The Swarm Corporation
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