Automating Multi-Currency EA Optimization with a Database Queue

Summary

The article outlines an architecture for automating optimization of one trading strategy across several symbol and timeframe combinations. It organizes work as a hierarchy: a project contains stages, stages contain jobs, jobs contain optimization tasks, and tasks record completed optimization passes. A database stores configuration, results, and status so an optimizing EA can find queued work and produce an initialization string for a universal EA.

The described prototype handles a single optimization stage and runs tasks sequentially; selecting and combining the best strategy instances and setting their group multiplier remain manual. The article reports that the process can resume from the next queued task after an interruption and preserve pass results. It also notes that project and stage status updates and multi-stage execution are not yet implemented. The example concerns several currency pairs and timeframes, but the document is primarily about optimization workflow and record keeping, not a tested trading signal or evidence of profitability.

Key ideas

• The proposed system stores optimization projects and their work items in a database hierarchy.
• An optimizing EA processes queued tasks and records results from each completed optimization pass.
• A universal EA can use a generated initialization string to load selected strategy instances.
• The current workflow automates a single stage, while selecting and combining instances remains manual.
• The article identifies unfinished project and stage status handling and multi-stage execution as limitations.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.