Owen Hobbs
Trading Systems · AI Architecture · Scalable Design
Ex-Head of Trading & Product Platforms · CoinAlpha
I built a three-layer AI agent platform that manages live algorithmic trading — from autonomous research through deployment to 24/7 monitoring.
Return
24-mo backtest
—
Sharpe
Risk-adjusted
—
Max Drawdown
Risk control
—
Win Rate
Consistency
—
Results
ProScore2 · Mar 2024 – Mar 2026 · IS/OOS validated
Return
—
Win Rate
of trades profitable
—
Sharpe Ratio
risk-adjusted return
—
Max Drawdown
worst peak-to-trough drop
—
What I Built
Autonomous Research
Agents test trading hypotheses through iterative experimentation — baseline measurement, parameter optimization, walk-forward validation. Budget-constrained with quality gates on every action.
Multi-Exchange Trading
Live on dYdX v4 and Hyperliquid with automated risk controls, circuit breakers, and a webhook pipeline feeding real trades to this dashboard.
Deterministic-First Monitoring
Three-layer system: free deterministic checks do the heavy lifting, LLM analysts handle anomalies on-demand, rule-based router orchestrates. 24/7 autonomous with crash recovery.
The Pivot
the architecture decisionBuilt 6 Claude-powered agents for 24/7 monitoring. Then realized: 95%+ of monitoring cycles find nothing wrong. Paying an LLM to confirm "everything is fine" is wasteful. Rebuilt as a three-layer architecture — deterministic checks first (free, instant), LLM analysts only when anomalies require reasoning. Same coverage, 93% lower cost.
What It Does Today
The research agent takes a trading hypothesis and autonomously tests it — from baseline measurement through parameter optimization to IS/OOS walk-forward validation.