the-swarm-corporation/autohedge

Build your autonomous hedge fund in minutes. AutoHedge harnesses the power of swarm intelligence and AI agents to automate market analysis, risk management,...

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Summary Information

Updated 55 minutes ago
Added to GitGenius on September 11th, 2026
Created on December 10th, 2024
Open Issues & Pull Requests: 22 (+0)
GitHub issues: Enabled
Number of forks: 870
Total Stargazers: 6,026 (+0)
Total Subscribers: 45 (+0)

Repository Insights (GitGenius)

Median issue/PR response: N/A
Mean response time: 48.5 days
90th percentile: 142.8 days
Tracked items: 4

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Issue Activity (beta)

Open issues: 8
New in 7 days: 3
Closed in 7 days: 0
Avg open age: 66 days
Stale 30+ days: 4
Stale 90+ days: 1

Recent activity

Opened in 7 days: 3
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

AutoHedge is an autonomous agent hedge fund that automates market analysis, risk management, and trade execution through swarm intelligence and specialized AI agents.

The tool addresses the challenge of executing sophisticated trading strategies at scale by decomposing the problem into specialized agent roles. A Director Agent generates trading theses and strategies, a Quant Agent performs technical and statistical analysis, a Risk Management Agent handles position sizing and risk assessment, and an Execution Agent generates and submits orders. The system integrates live market data, applies risk-first principles before any execution, and produces structured JSON outputs for downstream systems. Enterprise-grade logging provides audit trails and debugging capabilities.

AutoHedge suits developers and institutions building autonomous trading systems who want a modular, extensible framework rather than building from scratch. The tool currently supports full autonomous trading on Solana, with Coinbase and additional exchanges planned. The multi-agent architecture allows customization of individual agents and strategies while maintaining the overall pipeline structure. The risk-first design ensures position sizing and risk assessment occur before orders execute, addressing a critical concern in automated trading systems.

The project maintains active development with structured contribution guidelines and community support channels. The codebase emphasizes modularity and extensibility, allowing developers to add custom strategies and integrate new trading venues. Detailed logging and structured outputs reflect a focus on institutional reliability and auditability. The framework is built on top of an established AI agent platform, providing a foundation for the multi-agent coordination required in the trading pipeline.