This tutorial builds an XGBoost model for Nifty direction. Step 1: pull underlying and chain. Step 2: compute atm_iv, pcr_strikes, oi_buildup, vix_india, max_pain_distance, all lagged one bar. Step 3: label next-day direction. Step 4: walk-forward train with max_depth 5, subsample 0.8. Step 5: apply the risk filter (band 0.58-0.80, VIX z<2, max-pain>0.3%, DTE>1). Step 6: journal and review.
The edge is the feature work and the filter, not XGBoost itself. Publish the feature definitions and the leakage audit. Most '90% accurate' notebooks leak; this one lags properly and shows out-of-sample honestly. Use it as a research starting point, not a signal to risk capital blindly.
Q: What is the first step?
A: Pull clean underlying and chain data from a retail feed.
Q: How to avoid leakage?
A: Lag every feature one bar versus the next-day direction label.
Q: What filter gates the trade?
A: Band 0.58-0.80, VIX z<2, max-pain>0.3%, DTE>1.
Q: Is this a signal to trade?
A: No — a research method; validate and size before any capital.
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By Shakti Tiwari · Options AI research pillar. NISM XII certified. Educational only, not investment advice; verify before acting.