QuantQAlgo Technologies Pvt Ltd · Est. 2021

Trading decisions,
reduced to evidence.

We design systematic trading strategies, test them honestly against historical market data, and automate the ones that survive. And we teach the same methods to traders and institutional teams who would rather build than guess.

  • Strategy research
  • Backtesting & validation
  • ML / AI modelling
  • Execution automation
  • Training & workshops

About us

A research desk, not a tip service.

QuantQAlgo Technologies Pvt Ltd is a quantitative research and technology firm. We work at the point where market intuition has to become something measurable: a defined rule, a tested edge, a piece of code that behaves the same way on a bad day as it does on a good one.

Most trading ideas fail quietly. They look convincing on a chart, survive a flattering backtest, and then fall apart in live markets because nobody asked the hard questions — about costs, about slippage, about whether the result was ever anything more than noise. Our entire process is built around asking those questions early, while they are still cheap to answer.

We build for individual systematic traders, proprietary desks and corporate teams, across the intermediate-to-advanced range: from cleanly specified rule-based systems through to machine-learning and AI-assisted models where the data genuinely supports them.

  • Evidence before conviction

    Out-of-sample testing, walk-forward analysis and cost modelling are part of the build, not an afterthought. If an idea does not survive scrutiny, we say so.

  • Risk is the first design decision

    Position sizing, exposure limits and drawdown controls are specified before entry logic is ever optimised. A strategy you cannot hold through a bad month is not a strategy.

  • Nothing is a black box to you

    You receive the logic, the assumptions, the test methodology and the code. Where we build it for you, you own it.

  • Education that transfers

    Our workshops teach method — how to form a hypothesis, test it and reject it — rather than selling signals. The goal is that you stop needing us.

From the founder

A backtest is an argument, not a promise.

Eleven years in the financial markets — as a quantitative analyst, an algorithmic trading consultant and a teacher. I founded QuantQAlgo in October 2021.

Most trading ideas do not survive an honest test. That is the whole business: we test properly, we cost every assumption, and we tell you when an idea does not work. We publish no returns and we promise none.

The workshops exist for the same reason. I would rather teach fifty people to test their own ideas than sell the same signal to fifty people.

If you are building something systematic, write to me.

Kakal Krishna Rao

Founder & Managing Director, QuantQAlgo Technologies Pvt Ltd ·

Quant analyst, algo consultant and trading educator · 11+ years in financial markets

Services

What we build, and what we teach.

Two halves of the same practice. Engagements are scoped individually — most begin with a short paid discovery so that both sides know what is actually feasible.

01 Quant & algo engineering

Strategy design & development

We turn a thesis — yours or one developed jointly — into a fully specified system: entries, exits, filters, sizing and risk limits, documented so the logic is unambiguous before a line of code is written.

  • Trend, mean-reversion, momentum, volatility and spread structures
  • Equities, futures, options and currencies
  • Intraday through positional horizons

Backtesting & validation

Historical testing built to find the flaws, not to flatter the idea. We model brokerage, taxes, slippage and liquidity, and we separate the data used to build from the data used to judge.

  • In-sample / out-of-sample separation and walk-forward analysis
  • Monte Carlo and parameter-sensitivity stress testing
  • Survivorship, look-ahead and overfitting checks

Machine learning & AI models

Where the problem warrants it, and only then. Feature engineering, model selection and rigorous validation — with a clear-eyed view of how little signal most financial data actually contains.

  • Feature design from price, volume and derived market structure
  • Classification and regression models with leakage-safe validation
  • Regime detection and ensemble methods

Execution automation

Deployment against your broker's API, with the operational plumbing that decides whether a good strategy survives contact with live markets.

  • Order routing, retries and reconciliation
  • Kill switches, exposure caps and failure alerting
  • Logging and post-trade reporting for review

Automated order placement is routed through your SEBI-registered broker and remains subject to the exchange and broker approvals that apply to you.

02 Training & workshops

Retail workshops

For individual traders who already understand the markets and want to work systematically. Small cohorts, taught live, built around doing the work rather than watching someone else do it.

  • Hypothesis formation and data handling
  • Building and stress-testing your own system
  • Reading a backtest critically — and knowing when to discard one

Corporate & institutional training

Structured programmes for broking firms, treasury desks, fintech engineering teams and finance faculties. Delivered on site or remotely, and shaped around your stack and your people's starting point.

  • Curriculum mapped to your team's existing tooling
  • Cohort sizes and schedules to suit desk operations
  • Hands-on projects using your own historical data

How we work

Four stages, in order, every time.

  1. 01

    Discovery

    We establish the objective, the markets, the capital and risk constraints, and the operational reality you are trading within. Some ideas end here — which is the cheapest possible outcome.

  2. 02

    Research

    Data is sourced, cleaned and examined. The hypothesis is specified precisely enough to be proven wrong, then tested against history with costs and frictions included.

  3. 03

    Validation

    Out-of-sample testing, walk-forward runs and stress scenarios. You get the full methodology and the uncomfortable numbers alongside the encouraging ones.

  4. 04

    Deployment

    Implementation against your broker's API, paper-traded first, then moved to live capital at a size you choose — with monitoring, alerting and a documented handover.

Questions

Before you write to us.

Do you give buy or sell recommendations?

No. We do not provide trading tips, stock recommendations, portfolio advice or any form of investment advisory service, and we do not manage anyone's money. Our work is research, software engineering and education. If you need personalised investment advice, please consult a SEBI-registered Investment Adviser or Research Analyst.

Will a strategy you build make me money?

We cannot promise that, and you should be wary of anyone who does. Historical testing describes what a set of rules would have done in the past under a set of assumptions. It is evidence, not a forecast. Trading in securities and derivatives carries a real risk of loss, including loss exceeding your initial capital in leveraged products.

Who owns the strategy and the code?

You do. For bespoke development engagements, the logic, the documentation and the source code are delivered to you and the intellectual property is assigned to you on completion. We do not resell a client's bespoke work to anyone else.

Do I need to know how to code?

Not for development engagements — that is what we are for. For workshops, comfort with basic Python helps considerably, and our foundation modules cover what you need. Corporate programmes are pitched to the level of the cohort.

Which markets and data do you work with?

Primarily Indian equities, index and stock derivatives and currency futures, with selected global markets on request. We work with licensed historical data and with data you already hold. For teaching material we use delayed and historical data only.

How does this fit SEBI's algo trading framework?

Automated strategies are deployed through your own broker relationship and remain subject to SEBI's framework for retail participation in algorithmic trading, including broker-level registration and exchange-issued algo identifiers where those apply. We build with those requirements in mind, and we will tell you plainly where an approval sits with your broker or the exchange rather than with us.

What does an engagement cost?

It depends entirely on scope, and we would rather quote honestly than publish a number that means nothing. Development is typically fixed-fee per milestone; training is priced per cohort or per programme. Tell us what you are trying to do and we will come back with a written proposal.

Contact

Tell us what you are trying to build.

The more specific you are about markets, capital and timeframe, the more useful our first reply will be. We answer every genuine enquiry, usually within one working day.

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