06-23
How To Use Loop Engineering To Build A Self-Improving Quant Trading System
Written by a backend developer working on quant trading systems, this article argues for moving beyond manual prompt-and-wait workflows to building self-running loops. It dissects six universal components of production loops: automation hooks, skill files (SKILL.md), state files (STATE.md), a separate verifier agent, Git worktrees for isolation, and MCP-based connectors. The author then wires these around the five-stage quant trading cycle (data ingestion, signal generation, verification, execution, risk monitoring), with a feedback mechanism that writes lessons back into the skill file for continuous improvement. Targeted at engineers building AI-driven or automated systems, especially in finance.