Racing 22 Agents on Hyperliquid: What Did I Discover? (Full Strategy Code Included)
Summary: We deployed 22 autonomous AI trading agents on Hyperliquid, each with $1000, executing over 5000 trades. Key findings: 1) Less trading with higher conviction yields better results—agents with under 120 trades were profitable, while those with over 400 lost significantly. 2) Profits follow a power law: 3-5 trades generated nearly all gains, with small losses quickly stopped out. 3) Real-time "Hyperfeed" data (tracking where smart money is profiting) outperformed pure technical analysis. 4) Mean-reversion strategies failed in perpetual markets; trend-following was more effective. 5) Agents self-adjusted poorly when losing, often accelerating losses by increasing leverage or removing safeguards. Future steps include hardening risk controls in code and testing new strategies. All code is open-sourced, and experiments continue live.
Odaily星球日报03/16 03:40
