autohedge-swarm

# autohedge-swarm USE FOR: - "autonomous hedge fund agent" - "swarm agents for trading" - "director + quant + risk manager pipeline" - "Solana autonomous trading" - "enterprise AI trading system" - "risk-first automated trading" tags: [swarm, agents, hedge-fund, autonomous, Solana, risk-and-portfolio, enterprise, multi-agent, quant] kind: framework category: quant-ml-trading --- ## What Is AutoHedge? Enterprise-grade autonomous agent hedge fund using **swarm intelligence**. Specialized agents sequentially handle strategy, analysis, risk, and execution. - Repo: https://github.com/The-Swarm-Corporation/AutoHedge - Install: `pip install -U autohedge` - Current: Solana trading (Coinbase planned) - Philosophy: **Risk-first** — position sizing happens before execution --- ## Swarm Agent Pipeline ``` Director Agent ↓ Strategy generation + market context Quant Agent ↓ Quantitative analysis + signal generation Risk Manager Agent ↓ Position sizing + risk assessment + approval Execution Agent ↓ Order construction + submission Trade Output (JSON) ``` --- ## Installation ```bash pip install -U autohedge ``` **Environment variables:** ```bash JUPITER_API_KEY="..." # Solana DEX aggregator OPENAI_API_KEY="sk-..." # or ANTHROPIC_API_KEY WALLET_PRIVATE_KEY="..." # Solana wallet ``` --- ## Usage ```bash autohedge ``` Or programmatically: ```python from autohedge import AutoHedge fund = AutoHedge( llm_provider="anthropic", # Director/Quant use Claude risk_threshold=0.02, # Max 2% portfolio risk per trade chain="solana", ) result = fund.analyze_and_trade("SOL/USDC") print(result) # JSON: analysis + decision + risk metrics ``` --- ## Agent Responsibilities | Agent | Role | |-------|------| | **Director** | Market context, strategy selection | | **Quant** | Price analysis, signals, technicals | | **Risk Manager** | Position sizing, max drawdown limits | | **Execution** | Order construction, submission | --- ## Output Format (JSON) ```json { "ticker": "SOL/USDC", "director_analysis": "Bullish momentum...", "quant_signals": {"rsi": 58, "macd": "bullish"}, "risk_assessment": {"position_size": 0.015, "stop_loss": 0.02}, "decision": "BUY", "execution": {"order_type": "market", "size": 10.5} } ``` --- ## Key Design Principles 1. **Risk-first**: Never execute without risk approval 2. **Audit trail**: Enterprise logging at every step 3. **Modular**: Swap any agent or add custom stages 4. **Structured outputs**: All agents return JSON for system integration ---