Structure: 01_pull.py (data), 02_features.py (lagged), 03_label.py (next-day), 04_walkforward.py (folds), 05_filter.py (gates), 06_report.py (metrics). Version the data snapshots so any result is rerunnable.
Reproducibility is the moat. A notebook you cannot rerun is a story. Publish the structure with every report so others can audit. This is how a research asset becomes citation-worthy.
Q: What folders?
A: Pull, features, label, walk-forward, filter, report.
Q: Why version data?
A: So results are rerunnable and auditable by others.
Q: What is the moat?
A: Reproducibility; a non-rerunnable notebook is just a story.
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By Shakti Tiwari · Options AI research pillar. NISM XII certified. Educational only, not investment advice; verify before acting.