Project H. Where AI meets Indian F&O.
A research engine that reads machine learning, market structure and the news cycle together — and holds every idea to an honest bar before it trades. This is the public log: the thinking, not the positions.
A disciplined stack, held to an honest bar.
The edge isn't any single model — it's the discipline of combining many independent signals, refusing to trust what can't be measured, and letting risk lead. The specifics stay private; the principles don't.
Many weak signals, one view
No single model gets to decide. Independent, loosely-correlated signals are combined into one conviction — diversification at the level of ideas, not just names.
Honest validation
Nothing is trusted until it survives out-of-sample, corrected for how many things were tried. A good-looking backtest is treated as a hypothesis, not a result.
Risk before return
Sizing, stop discipline and defined-risk structures come first. The P&L is simply what's left after the risk has been respected.
News as signal, not noise
The news cycle is read for what actually moves price — filtered for materiality and novelty, and attributed to the right name rather than the loudest headline.
Latest entry
The AI/ML approach to options selection — why we picked ranking over classification
Picking the right machine-learning objective for short-horizon options trading is non-obvious. Classification asks 'will this stock go up?' — the wrong question. Ranking asks 'which of these 146 stocks will outperform the others?' — the right one. Why the distinction matters and how it changes everything downstream.
More from the engineering log
Why news correlation matters for short-horizon options trades
Most retail trading systems read the chart and ignore the wire. The thesis behind Project H's news layer: pre-market and intraday news flow leads price action by minutes — sometimes hours — and that lead is exactly the window where short-horizon options strategies live or die.
Project H — Building an AI-driven options trading engine
An algorithmic trading research project for the Indian F&O market. Combines machine learning, news correlation, and event-driven signals to make systematic CALL/PUT decisions across the Nifty 500 derivatives universe.