From research signal to live execution checklist

A research signal is not ready for live trading simply because its backtest looks good. Graduation requires evidence across data quality, regime robustness, execution feasibility, and operational monitoring.

Our checklist starts with reproducibility: can the result be regenerated from stored data and versioned parameters? Next comes stability: does performance depend on one narrow date range or one unusually favorable asset? Then execution: does the signal survive realistic spread, slippage, and latency?

Finally, the live candidate needs observability. Every decision should leave enough context to explain why the model acted, what risk layer approved, and how the exchange response compared with expectation.

This process slows down deployment, but it reduces the odds of confusing a research artifact with a tradable edge.