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The-Swarm-Corporation/AutoHedge

Autonomous trading agent system

+50 stars in 7 days

Build an automated trading system on Solana where AI agents handle market analysis and order execution

You can build a system in minutes that analyzes real-time market data on the Solana network, calculates risk, and places orders automatically. The structure involves multiple AI agents dividing roles to create and execute investment strategies. While it currently supports only Solana, integration with other exchanges like Coinbase is in preparation.

Agent pipeline with divided roles

The system does not rely on a single AI to do everything; instead, multiple agents with divided roles operate in a pipeline. A director agent creates investment strategies and hypotheses, while a quant agent performs technical and statistical analysis. Subsequently, a risk manager determines position size and risk level, and finally, an execution agent generates and sends orders. The results of each step are structured in JSON format and passed to the next stage, with the entire process recorded in detailed logs.

Supported exchanges and installation

The only exchange available for immediate use is Solana. Coinbase is under development, and other centralized exchanges are on the roadmap. Installation is performed in a Python environment using the pip install -U autohedge command. To run it, you must set the Jupiter API key, an OpenAI or Anthropic API key, and the wallet's private key as environment variables. The default usage is simply entering autohedge in the terminal.

An option for Solana traders

This tool is suitable for those who want to try automated trading in the Solana ecosystem. It is useful when manually checking market data and placing orders is cumbersome, or when consistent risk management is needed. However, since it is currently limited to Solana, you must wait to handle other chains or exchanges simultaneously. Additionally, because it relies on the judgment of AI agents, thorough testing and log verification are essential before deploying real funds. It is released under the MIT license, allowing for code modification and extension.

Written by AI from this repository's README on September 27, 2026. For the facts, the original on GitHub is the reference.

By the numbers

GitHub trending history
3 days between Jun 19, when Trend began recording, and Nov 8, 2026 · first on Sep 6 · best daily rank #8 (Sep 7)

Read from GitHub, as of November 8, 2026.

Language
Python
Topics
ai · blackrock · finance · goldmansachs · hedgefund · jpmorgan · ml · quant
Stars
6,646
Stars gained in 7 days
+50
Contributors
2
Forks
968
Commits
37
Last commit
March 5, 2026
Open issues
11
Open pull requests
15

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