Quantitative investment firm

Algorithm-driven strategies, built for sophisticated investors.

We design systematic trading models for India's equity and derivatives markets. Every model earns its capital by surviving years of historical testing before it places a single live order.

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Why QFI

Where edge meets execution.

Discretionary investing runs on conviction. We run on evidence. Every position QFI takes is the output of a measured process, and human judgement is held back for oversight rather than spent on guesswork.

Execution

Algorithmic trading

Trading logic that reads market microstructure and acts in milliseconds, taking hesitation and manual error out of the loop.

Validation

Strategy backtesting

Models are simulated across years of history and stressed through past regimes before they are trusted with capital.

Allocation

Portfolio management

Exposure, rebalancing and capital allocation adjust continuously against the risk targets set for each mandate.

Coverage

Multi-asset support

Equities, index derivatives and volatility instruments run inside one systematic framework across Indian markets.

Two philosophies

The same market, read two ways.

Traditional

Read the story

A view forms from news, intuition and experience. It shifts with the mood of the day, and the same setup can produce a different decision on a different morning. Results are hard to attribute, and harder to repeat.

OUTCOME DEPENDS ON THE PERSON

QFI systematic

Measure the signal

A rule is written, tested against history, and given a fixed risk budget. It behaves the same way on a calm Tuesday as it does in a selloff, because nothing about it changes with the mood of the day.

OUTCOME DEPENDS ON THE PROCESS

Investment process

From raw market data to a live order.

STEP 01

Data and signals

Clean market data feeds a research library of statistical signals built from years of Indian market history.

STEP 02

Backtest and validate

A signal becomes a strategy only after it survives out of sample testing with realistic costs applied.

STEP 03

Risk and execute

Position sizing, risk limits and automated execution operate as one connected system.

Explore the full process

By invitation

Built for a limited number of investors.

We partner selectively with high net worth and institutional investors who value process over promises. Begin with a private, no obligation conversation.

Request private consultation

Our strategy

Investment philosophy

Markets are competitive, noisy, and only partly efficient. A durable edge never comes from one clever idea.

It comes from an engineered process. Disciplined research, honest validation, and risk control applied the same way on the best day of the year and the worst one.

Evidence over opinion

A strategy earns capital when the data supports it across regimes, however compelling the story around it happens to sound. We have killed ideas we liked because the numbers did not agree.

Process over prediction

We do not forecast the market. We build repeatable systems with a measurable statistical edge, then let them run long enough for that edge to show up.

Risk before return

Capital preservation is the first constraint, not a footnote. Sizing and drawdown limits are set before anyone talks about a profit target.

Automation over emotion

Machines execute what the research decides. No hesitation, no fatigue, and no quiet renegotiation of the rules at 3pm on a bad day.

Regime framework

Our models classify the market before they trade it.

Most strategies fail because they assume one kind of market and then meet another. We treat the regime as an input, and it decides which models are allowed to run at all.

Trending, low volatility

Momentum leads

Trend following models take the front seat. Noise is low, so stops are less likely to be triggered by nothing.

Range bound

Mean reversion leads

Price oscillates around fair value, and strategies that fade the extremes do the work.

High volatility

Everything tightens

Exposure comes down, stops widen, and position sizing shrinks automatically. Survival comes first.

The pipeline

How a signal becomes a live position

01

Data infrastructure

Tick, minute and daily data across NSE instruments is ingested, cleaned and normalised into a research ready store. Most of the hard work in quant happens here, and it is the least glamorous part of the firm.

02

Signal research

Researchers mine statistical relationships across momentum, mean reversion, volatility and cross sectional structure, looking for behaviour that persists rather than behaviour that merely happened.

03

Backtesting

Candidates are tested out of sample with realistic costs and slippage applied. Only models that hold up across regimes go forward. Most do not.

04

Risk framework

Approved strategies receive position limits, drawdown controls and a share of the portfolio exposure budget before they are allowed near live capital.

05

Automated execution

Orders route through our execution engine, which optimises for fill quality and keeps market impact low.

06

Monitoring

Live results are compared against expectation every single day. When an edge decays, the model is retired without sentiment.

Technology

The systems behind the strategy

QFI is an engineering firm as much as an investment firm. Our edge is written, tested and maintained in code.

Research

Quantitative research

A Python first environment for signal discovery, statistical modelling and hypothesis testing.

Python / NumPy / pandas / statsmodels

Intelligence

Machine learning

Learning systems for feature engineering, pattern recognition and classification of the prevailing market regime.

scikit-learn / PyTorch / XGBoost

Validation

Backtesting engine

Event driven simulation with cost, slippage and latency modelled honestly, so results survive contact with the market.

Walk forward / Monte Carlo / cost models

Data

Data infrastructure

Low latency ingestion and a time series store that serves research and live trading from one source of truth.

Time series DB / market feeds / pipelines

Execution

Execution and OMS

Automated order and execution management, with routing designed to keep market impact low.

Order management / smart routing / broker APIs

Control

Risk systems

Real time exposure, drawdown and limit monitoring that can throttle or halt any strategy without waiting for a human.

Real time risk / limits / kill switch

See the philosophy in the numbers.

Our process is designed to be measured. Review how these principles translate into portfolio performance and risk.

See how we control risk

Risk and reporting

Risk is the first constraint

Most firms show you the returns and describe the risk afterwards. We size the risk first, and the returns are whatever that discipline allows.

Any strategy can look good for a quarter. What decides whether a firm is still here in ten years is what happens when it is wrong, and how quickly the system notices. This page describes the controls that sit between a model and your capital.

LAYER 01

Before the model ever trades

Nothing reaches live capital without surviving out of sample testing with realistic costs, slippage and latency applied. Most candidates die here, which is the point. The cheapest loss is the one taken in a simulation.

LAYER 02

Position sizing and limits

Every approved strategy is issued a fixed risk budget, a maximum position size, and a share of total portfolio exposure. The budget is set before the strategy runs, so no one is deciding how much to risk while a trade is moving against them.

LAYER 03

Regime-aware throttling

Exposure is not constant. As realised volatility rises, position sizing contracts automatically and the classifier can stand strategies down entirely. The system reduces risk without waiting for anyone to agree that it should.

LAYER 04

Drawdown controls and kill switch

Each strategy carries a drawdown limit that halts it without discussion. Real time monitoring watches exposure and limits across the whole book, and any strategy can be throttled or stopped in full, immediately.

Mechanism

When volatility rises, exposure comes down

Volatility against exposureschematic

REALISED VOLATILITY PERMITTED EXPOSURE

This is a diagram of the rule, not a record of results. It shows the relationship the system enforces: as measured volatility climbs, the exposure the book is permitted to carry steps down, and it steps back up only once conditions settle.

The response is mechanical. It does not require a meeting, a view on where the market goes next, or the willingness to act against your own position. That is the whole argument for doing this systematically.

Reporting

What our investors actually receive

Transparency is a schedule, not a slogan. Investors know what arrives, and when.

ContinuousLive exposure and risk monitoringPositions, limits and drawdown watched in real time across the book.

MonthlyPerformance statementReturns for the period, net of costs, with the risk taken to earn them.

MonthlyAttribution and exposure breakdownWhich strategies contributed, where the book was positioned, and why.

QuarterlyPortfolio reviewA direct conversation covering results, changes to the models, and anything retired.

On requestAudited track recordThe complete verified history, shared directly with prospective investors.

ON THE TRACK RECORD

We do not publish performance figures on this website. Indian regulation sets a high bar for how returns may be presented, and numbers stripped of their context and risk tend to mislead more than they inform. The full audited record is shared directly with qualified investors during a private consultation.

Ask us for the numbers.

The complete audited track record, attribution and risk reporting are shared directly with prospective investors. Start with a private conversation.

Request the full track record

Why quantitative investing

The case for a systematic approach

In India, quant investing is still widely misunderstood. The idea behind it is not complicated.

Replace guesswork with a disciplined, data driven process, and let evidence decide instead of emotion. Everything below follows from that one move.

The limits of traditional investing

Decisions bend to emotion, recency, and whatever story the market is telling that week. Human execution is slow and inconsistent, and it degrades exactly when conditions get difficult.

Strategies are rarely tested, so conviction stands in for evidence. Risk gets handled after losses appear rather than before, and performance is difficult to attribute, repeat or scale beyond the person who produced it.

The advantages of quant investing

The same rules apply in every market on every day, so bias has nowhere to enter. Automated systems act in milliseconds rather than minutes, and every position traces back to tested evidence.

Limits and drawdown rules run continuously in the background rather than waiting for someone to notice. Returns come from a documented process that any qualified team can audit, which is what makes them repeatable and scalable.

Point by point

Systematic against discretionary

For HNI and institutional investors

What this means for your capital

Discipline you can audit

Because every decision follows an explicit rule, performance can be measured and explained rather than credited to instinct or luck.

Risk shaped to your mandate

Exposure and drawdown limits are engineered around your risk tolerance and enforced automatically in every market condition.

A different return driver

Systematic strategies can behave differently from a traditional equity portfolio, adding a genuinely separate source of return.

Institutional standards

Clear performance and risk reporting, at the level of accountability a sophisticated investor should expect from any manager.

Bring us a portfolio and a question.

The fastest way to understand whether this approach fits is to talk through your mandate with the people who built it.

Discuss your portfolio

About QFI

Research culture, real world problems

We started QFI on one conviction: that deep research and real engineering, applied to India's markets, produce an edge discretionary investing cannot reach.

The firm began in Hyderabad with a single trade. What has not changed since is the culture. Technical, rigorous, and unwilling to accept an idea because it sounds right.

Our edge

What makes us different

01

Quantitative depth

A dedicated research process that turns market data into tested, statistically grounded strategies, using the same discipline as leading global systematic firms.

02

Systematic models

Rules based strategies that adapt to the prevailing regime instead of reacting to headlines.

03

In-house execution

Proprietary execution and risk systems rather than off the shelf tools, which gives us direct control over speed, cost and safety.

04

India specialisation

Built entirely around the structure, liquidity and microstructure of Indian equity and derivatives markets.

Leadership

The people who set the direction

FOUNDER'S NOTE

Ajay Biradar

CEO and Founder

IIIT Hyderabad / NSE

I am Ajay, founder of QFI Capital.

I believe the best returns don't come from predicting markets. They come from disciplined systems that manage risk before they chase reward. That conviction has shaped everything about how I think, built over two decades across capital markets, banking, and financial services, along with a background from IIIT Hyderabad.

Most traders are wired to react, chasing signals instead of following process. That gap is what led me to build QFI Capital: AI-powered algorithmic trading systems for the Indian equity derivatives market, built to bring institutional-grade discipline to a market that has never had access to it.

We're not building another signal service or a black box. We're building systems that read the market with data and structure, execute with consistency, and treat capital protection as seriously as returns.

Today, QFI Capital exists to bring that discipline to Indian traders and investors, turning complexity into clarity, and conviction into consistent execution.

Ajay FOUNDER, QFI CAPITAL

IN HIS OWN WORDS

Baibhab Kumar Mustafi

Quant Backend Systems Head

BITS Pilani / Samsung

As the Quant Backend Systems Head at QFI Capital, I architect the high-performance infrastructure that powers our cutting-edge algorithmic trading and AI research. Building on my engineering foundation from BITS Pilani and early experience at Samsung, I specialize in developing robust backend systems and complex algorithmic data pipelines.

My primary focus is on designing scalable, low-latency architectures capable of executing advanced quantitative models and managing massive datasets in real time. By bridging the gap between deep technical engineering and financial technology, I am dedicated to driving QFI Capital's mission forward in the modern, data-driven trading era.

Professional headshots should replace the plain type treatment here before launch, as the redesign brief recommends.

Offices

HEADQUARTERS

Hyderabad

Where it all began, with our very first trade. Hyderabad remains our research and trading base, and the centre of everything the firm builds.

OFFICE

Ahmedabad

Our second location, supporting engineering and operations as the firm grows across India.

Come and see how we work.

The clearest picture of the firm comes from a conversation, not a page. We are happy to walk you through the process in detail.

Request private consultation

Research and insights

Our view of the markets

We publish work on market structure, volatility and the state of quantitative investing in India. It is the clearest window into how the firm actually thinks.

Quant world / Featured

Regime detection: teaching a model to know which market it is in

Most strategies do not fail because the signal was wrong. They fail because the market changed underneath them and nobody told the model. This piece walks through how we classify regimes, and what it costs when you get the classification late.

14 min read

Weekly market outlook

What we are watching

WK 28 / 2026Nifty pins toward max pain into a quiet Tuesday expiry

WK 27 / 2026India VIX compresses, and what a low volatility regime means for momentum

WK 26 / 2026Bank Nifty on monthly expiry only: three months of structural read through

WK 25 / 2026Gift Nifty gaps and the overnight information they price in

Sample titles. Connect this list to your research publishing workflow.

Read the research before you trust the firm.

Published work is a fraction of what our investors receive. Request access to the full research library and weekly outlooks.

Request research access

Careers

Build the systems behind the strategy

We are a small team of engineers and researchers who take markets, code and evidence seriously. If you want ownership, hard problems, and a culture that rewards rigour, we should talk.

Research

Quant research

Discover, test and refine the statistical signals that drive our strategies across Indian equity and derivatives markets.

Quantitative Researcher, SignalsFull timeHyderabad

Quantitative Researcher, Derivatives and VolatilityFull timeHyderabad

Intelligence

Machine learning engineering

Build the learning systems behind feature engineering, regime classification and pattern recognition on market data.

Machine Learning EngineerFull timeHyderabad

ML Research InternInternshipHyderabad

Engineering

Python development

Own the research platform, the backtesting engine, and the internal tooling the whole firm runs on.

Software Engineer, Research PlatformFull timeHyderabad

Backend Engineer, Data SystemsFull timeAhmedabad

Systems

Trading infrastructure

Engineer the low latency execution, order management and risk systems that put strategy into the market.

Trading Systems EngineerFull timeHyderabad

Execution and Risk Infrastructure EngineerFull timeAhmedabad

Culture

What it is like to work here

A small, senior team, where your work ships and matters from the first week.
Evidence over hierarchy. The best tested idea wins the argument.
Deep focus on well defined problems sitting between markets and code.
Continuous learning across research, engineering and live trading.

Open application

No role that fits?

We are always interested in exceptional researchers and engineers. Send us your work and tell us what you would want to build here. We read everything that comes in.

Send an open application

Private consultation

Begin a private conversation

QFI works with a limited number of investors. Share a few details and our team will arrange a confidential, no obligation consultation to explore whether we are the right fit.

Request received.

Our team will review your enquiry and reach out within two business days to arrange your confidential consultation.