Your capital works once.
We make it work twice.
A long-term portfolio is productive and idle at the same time. The stock compounds. The margin locked behind it just sits there. We build the second engine that runs on that margin.
Nobody buys a flat
and leaves it empty.
Buy an investment property and you do two things with it. You let it appreciate, and you rent it out. One asset, two income streams. Everybody understands this.
Appreciates and earns rent
- Capital appreciation yes
- Rental income yes
Appreciates. Earns nothing else.
- Capital appreciation yes
- Income from the interest-free margin behind it nothing
Pledging your holdings is the equivalent of renting out the flat. You still own it. It still appreciates. It now also produces income.
The Double Engine
Your shares earn the market's return. The margin locked behind those shares earns nothing until you put a second engine on it. Same capital, nothing sold, two returns instead of one.
The stocks work
₹1 crore in NIFTYBEES earns whatever the index earns. Historically that has averaged about 12% a year.
The margin unlocks
Your broker releases trading margin against those holdings. You have not sold anything and you have not borrowed, so there is no interest to pay.
The second engine runs
That idle margin funds systematic option strategies on NIFTY and SENSEX. Its return stacks on top of the first.
Our proprietary algorithms
Three algos, written from scratch and traded with our own money. Each runs a basket of independent strategy sleeves rather than one setup. The sleeves disagree with each other by design, and that disagreement is what flattens the curve.
- Average month
- +3.47%
- Monthly income
- ₹3.41 L
- Annual income
- ₹40.96 L
- Maximum drawdown
- −4.95%
- Sharpe ratio
- 4.67
- Return / drawdown
- 34.4
- Months in profit
- 86%
Four years and several very different market regimes.
- Average month
- +6.24%
- Monthly income
- ₹6.24 L
- Annual income
- ₹75.43 L
- Maximum drawdown
- −4.40%
- Sharpe ratio
- 6.28
- Return / drawdown
- 44.0
- Months in profit
- 94%
Two indices with different expiry days. Every position carries a protective wing, which is what keeps the margin efficient.
- Average month
- +2.13%
- Monthly income
- ₹2.13 L
- Annual income
- ₹25.71 L
- Maximum drawdown
- −1.50%
- Sharpe ratio
- 6.28
- Worst month
- −0.47%
- Months in profit
- 94%
* Figures are backtested on ₹1 crore of deployed margin, net of 0.2% slippage per fill, the cost of the protective hedge, and all statutory charges. A backtest is not a live track record, and it is not a promise of future returns. These systems are built and run for our own capital. Full disclosures are below.
You set the drawdown.
The algo sizes itself.
Most systems hand you a return and leave the risk wherever it lands. Whale works the other way round. You name the deepest drawdown you are willing to sit through, and the position sizing is solved backwards from that.
Because sizing is the only thing that changes, the Sharpe ratio stays at 6.28 at every setting. You are moving along one risk-return line, not switching strategies.
Hedged the same way at every setting, so the margin per lot does not change. At 4.4% the algo runs unrestricted, with no size reduction at all.
AI does the searching.
Rules do the trading.
Every algo on this page survived a machine that spent weeks trying to break it. Millions of versions get built, tested against years of real market data, and thrown away. What we actually trade is the small handful that held up.
Search at scale
A person tests twenty ideas in a week. A machine tests three million, against years of real prices and real costs.
IS → OOS testing
Test three million settings and one looks brilliant by chance. So nothing ships until it still works on data it has never seen.
AI systems we build
Models that learn a signal, systems that read market conditions, and the research tooling around both. We build those too.
An algo development and consulting firm.
We are engineers, not advisors. We write trading software, test it honestly, and hand it over. The algos above are systems we built for our own capital, and the same work can be done for yours.
Strategy development
From an idea, or a rule you already trade by hand, to production code with stop-losses, re-entry logic and execution safeguards built in.
Backtesting that tells the truth
Slippage on both sides, statutory charges, real expiry calendars, walk-forward validation. We kill more ideas than we ship. That is most of the job.
Live execution systems
Broker-side stop-losses, fill confirmation, spike-trigger detection, entry repricing and a kill switch. These are the parts that decide whether a good backtest survives a live market.
The engineer and the trader
are the same person.
A seasoned algorithmic trader with hands-on experience in Indian index options and US SPX 0-DTE options and MNQ futures. Also a software engineer, which is why the systems get written here instead of outsourced.
Short-volatility and intraday expiry structures on NSE and BSE index options. Multi-year tick-level datasets, with our own execution stack running on live broker APIs.
0-DTE option structures on the SPX, and MNQ futures on the Nasdaq-100. Two different indices in a session that runs while India sleeps.
The markets teach different lessons. Indian index options are dense with expiry-day flow and structural quirks; SPX is deeper and far less forgiving of sloppy execution. A strategy that only works in one session's microstructure usually isn't a strategy.
On the engineering side: data pipelines, broker API integrations, and live order-management systems with native stop-losses and failure handling. Every algo here was built in-house, along with the backtester, the execution layer and this website.
Most trading-software shops can code but have never had money at risk. Most traders have conviction but no way to ship it. QuantNifty sits in the overlap, which is a narrower place than it sounds.
What people ask us first.
Straight answers about pledged margin, what we build, and what we are not.
How can I earn from my stock portfolio without selling it?
By pledging it. When you pledge shares or ETFs with your broker, the broker releases trading margin against their value while you keep ownership, dividends and long-term capital-gains treatment. That released margin can fund a separate options strategy, so the same capital produces two returns instead of one. Nothing is sold and nothing is borrowed.
What is pledged margin, and does it cost interest?
Pledged margin is collateral value your broker recognises against securities you already own. It is not borrowed money, so no interest is charged. Brokers apply a haircut, so ₹1 crore of holdings usually releases about ₹75 to 85 lakh of usable margin, depending on the instrument.
Is QuantNifty SEBI registered?
No. QuantNifty is not a SEBI-registered Research Analyst, Investment Adviser, Portfolio Manager or Broker. We are an algorithm development and consulting firm, so what we do is write and test trading software. We do not manage money, sell tips or signals, or give investment advice.
What is a good Sharpe ratio?
The Sharpe ratio measures return per unit of risk. Roughly speaking, a bank deposit sits near 0.3, buy-and-hold NIFTY near 0.6, a good equity mutual fund near 1.0, and a strong hedge fund near 2.0. Anything above 3 is rare. QuantNifty's backtested algos sit between 4.67 and 6.28 over their stated windows.
What does 0–1 DTE mean?
DTE means days to expiry. A 0-DTE trade is opened and closed on the contract's expiry day, and 1 DTE is the session before it. Both are intraday, so nothing is carried overnight and there is no gap risk between sessions.
Are the returns on this page live or backtested?
Backtested. Every figure is simulated on historical 1-minute data over the window stated on each algo, net of 0.2% slippage per fill, the cost of the protective hedge, and all statutory charges. A backtest is not a live track record. Live results will differ because of execution, liquidity, latency and changing market regimes.
Can I buy or subscribe to Apex, Alpha or Whale?
No. Those three systems run on our own capital and are shown to demonstrate engineering capability. They are not offered for sale, licensing or subscription. What we offer is development work: you bring a strategy or a requirement, we build, test and automate it for you.
Do you use AI or machine learning in your trading systems?
Yes, but in the research, not in the trading. Millions of versions of a strategy are generated and tested automatically against years of real market data, then filtered down to the few that still work on data they have never seen. The algos that go live are fixed rules: every entry, stop and exit is written in plain code you can read, so no model decides on its own when money moves. We also build learning systems for clients, including models that predict a signal and systems that detect which market conditions you are in.
How do you stop an AI search from overfitting?
Test three million settings and one will look brilliant purely by chance, the same way someone in a big enough crowd flips ten heads in a row. So we check whether the winners on old data are still winners on data they have never seen. On our SENSEX search across 3.2 million versions, they were not: finishing first on the old data told us nothing about what happened next. So the basket was not picked by taking the best score. It was picked from the setups that kept appearing across thousands of good results, because a pattern that repeats is much harder to fake than one lucky number. Every test also charges realistic slippage on both sides of a trade plus full statutory costs, so nothing looks good only because the costs were left out.
What does an algo development engagement actually include?
Turning a trading idea into production software: entry and exit logic, stop-losses, re-entry rules, position sizing, and honest backtesting with slippage, statutory charges and real expiry calendars. Where it is needed, live execution as well, which means broker-side stop-losses, fill confirmation, order repricing, spike-trigger detection and a kill switch.
What capital do these strategies need?
The figures on this page use ₹1 crore of deployed margin because it makes the arithmetic readable. The strategies themselves are sized in lots, so they scale down. A single NIFTY sleeve needs roughly ₹1.6 lakh of hedged margin. What matters more than size is that the drawdown is set to something you can actually sit through.
Which markets and instruments do you work with?
Indian index derivatives: NIFTY 50 options on the NSE and SENSEX options on the BSE. The algos shown trade short-volatility structures on the index straddle, filtered by a rolling VWAP signal, with per-leg stop-losses.
Tell us what you want built.
We will tell you honestly whether the idea is worth building before quoting anything.
Just message us
Skip the form. Send the idea in whatever shape it exists: a screenshot, a paragraph, a spreadsheet, a TradingView link.
What we do not do
We do not manage anyone's money, sell tips or signals, guarantee returns, or give investment advice. We are not SEBI registered. We write trading software to your specification, and you own the strategy decision along with the risk that comes with it.