XGBoost for NIFTY: Feature Engineering Deep Dive (83 Features Explained)
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The exact feature set behind a 67% win-rate intraday system — and why 83 features beat 150 Most retail ML trading tutorials use 10 to 15 features. RSI. MACD. Two moving averages. That is enough for a demo, but institutional algorithms eat that for breakfast. I run an intraday NIFTY system with 83 features across four categories: price action, volume flow, derivatives microstructure, and time-based regime filters. After running A/B tests against 150-feature and 30-feature variants, 83 is the…
1Key Takeaways
- The exact feature set behind a 67% win-rate intraday system — and why 83 features beat 150 Most retail ML trading tutorials use 10 to 15 features.
- That is enough for a demo, but institutional algorithms eat that for breakfast.
- I run an intraday NIFTY system with 83 features across four categories: price action, volume flow, derivatives microstructure, and time-based regime filters.
- After running A/B tests against 150-feature and 30-feature variants, 83 is the….
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that the exact feature set behind a 67% win-rate intraday system — and why 83 features beat 150 Most retail ML trading tutorials use 10 to 15 features.
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