A systematic edge in Indian markets, built in the open.
Project His an independent research engine for Indian F&O — dozens of systematic strategies, forward-tested on paper every session. The goal: find durable, repeatable edge, and prove every claim in the open before a rupee is ever at risk.
Paper-traded forward tests · no real capital · research, not investment advice.
Set a scenario — watch the signals become a view.
News and trend agree, and options are cheap — so it leans in harder.
Illustrative only — a toy of how the engine weighs signals into a view. Not the real model, not a prediction, not investment advice.
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.
Measured, never trusted
Nothing earns weight until it survives out-of-sample, corrected for how many things were tried. A good-looking backtest is a hypothesis, not a result.
Risk before return
Position sizing, stop discipline and defined-risk structures come first. The P&L is 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, attributed to the right name, and discounted when the market has already priced the move.
The scoreboard is public. Most aren't.
Anyone can claim a strategy works. This project publishes its paper scoreboard live instead — every experiment, marked against real market prices, refreshed through the session. The evidence accrues in public or it doesn't count.
Every run reports
No cherry-picked screenshots. The live board lists every experiment, its capital and its P&L — including the ones having a bad day.
Paper until proven
No real capital is deployed. Every strategy trades a simulated book marked against real market prices, and has to earn its keep out-of-sample before anything changes.
Research, not advice
This is the public log of a forward-testing experiment — not a signal service, not a tipsheet, and never investment advice.
The structure is public. The P&L stays private.
Here's the shape of the live book — how many strategies are under test, how long it's been running, what's been retired, and how many have earned real capital. No rupee figures here; the live P&L sits behind a login.
Latest entry
Ranking, not classification — framing the ML problem so it can be honest
The most consequential modelling decision in Project H isn't an architecture or a hyperparameter — it's the question the model is asked. 'Will this stock go up?' is the wrong question. 'Which names are likely to outperform their peers?' is the right one. Why the framing matters, and why honest validation matters more.
More from the log
Why news matters for short-horizon options trades
Most retail systems read the chart and ignore the wire. The hypothesis behind Project H's news layer: meaningful moves leave a trail in the news flow before they leave one on the chart — and short-horizon options are exactly where that lead matters. A hypothesis, not a claim: the forward test is the judge.
Project H — systematic options research, forward-tested in public
An independent research project for the Indian F&O market. Machine learning, news intelligence and event-driven mechanics feed one systematic book — every idea forward-tested on paper, with the scoreboard published in the open.
One person, one honest experiment.
Project H is an independent research engine for the Indian F&O market, built and run end-to-end by a single developer. Machine learning, a news-intelligence layer and event-driven mechanics feed one systematic, risk-led book — and every idea is forward-tested on paper, marked against real market prices, with the scoreboard published in the open.
There's no fund here, no product, no signal service. Just a narrow question, tested honestly: can a disciplined, systematic approach to Indian F&O hold up out-of-sample — and can the working be shown in public, wins and losses alike? When something doesn't earn its keep, it stays on the board anyway.