Use swarm intelligence and configurable agents to automate market analysis and hedge strategies.
Detailed Introduction
AutoHedge, developed by The Swarm Corporation, is an open-source project to build autonomous hedge systems quickly. It blends swarm intelligence concepts with orchestrated AI Agent components to automate data collection, signal generation, risk constraints, and trade execution. The framework emphasizes observability and cost transparency, adapts to multiple data sources and trading APIs, and helps quant teams validate and deploy strategies in an engineering-friendly way.
Main Features
- Swarm-driven signal aggregation that combines heterogeneous agent strategies via voting and synthesis.
- Strategy pipelines and risk management modules with configurable stop-loss, position limits, and guardrails.
- Multiple data sources and trading adapters for backtesting, real-time streams, and major exchange APIs.
- Developer-friendly: Python SDK, example scripts, and documentation for easy integration and extension.
Use Cases
- Rapid prototyping and production deployment of automated hedge fund strategies.
- Privacy- or compliance-sensitive deployments combining local models and auditable logs for traceability.
- Risk monitoring and automated compliance: rule-driven protective actions on anomalous events.
Technical Features
- Extensible agent architecture where each agent handles distinct signal sources or strategies and results are aggregated.
- Engineering-focused tooling: unified configuration, backtesting, simulation, deployment, and logging.
- Cost/performance tradeoffs: built-in metrics to evaluate model/strategy priority and execution cost for optimization.