Your backtest is lying to you
Point-in-time correctness is the difference between a financial ML pipeline that works and one that only appears to. Here is where the leaks hide and how to design them out.
Writing
Mostly things I got wrong first. Retrieval, evaluation, latency, and the data plumbing nobody puts in the demo.
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Point-in-time correctness is the difference between a financial ML pipeline that works and one that only appears to. Here is where the leaks hide and how to design them out.