Quantitative Intelligence
for Modern Markets.
We conduct quantitative research and build machine-learning models and research tooling for hedge funds, family offices and professional investors. Data. Research. Discipline.
Six disciplines, one research culture.
August Quants is built around the conviction that institutional-grade investing demands an engineering mindset, a research culture and a refusal to confuse activity with insight. Our work spans the full quantitative stack — from hypothesis to implementation.
Quantitative Research
Rigorous, data-led investigation of return drivers across equities, fixed income, FX and commodities.
Machine Learning Models
Production-grade ML pipelines, feature engineering and validation discipline calibrated for financial data.
Portfolio Construction Research
Methodology and decision-support for risk-budgeted, regime-aware portfolios — designed around horizon, drawdown tolerance and mandate. Clients build and decide.
Systematic Strategy Research
Trend, carry, mean-reversion and cross-sectional strategy research — designs and frameworks that clients implement themselves.
Market Intelligence
Institutional-grade synthesis of macro, micro and flow data. Signal over noise, always.
Bespoke Quant Solutions
Custom research engagements, model development and decision-support for sophisticated allocators.
From mandate to model to monitored allocation.
Understand
We start with mandate, constraints and intent — not with models. Every engagement begins with a structured discovery conversation.
Research
Hypotheses are framed, data engineered, signals tested with cross-validated discipline and capacity in mind.
Construct
Robust portfolios are built using risk parity, factor budgeting and regime-aware sizing — not point-estimate optimisation.
Deliver
Research output, documentation and an ongoing research dialogue. Clients implement and execute their own investment decisions.
Rigour is the only durable edge.
We believe markets reward intellectual honesty more than complexity. Most published “alpha” is statistical noise dressed in graphs. Most great strategies are simple ideas implemented with discipline.
Our research is shaped by four principles: every hypothesis must have a coherent economic explanation, every test must be honest about multiple-comparison risk, every model must respect capacity, and every portfolio must be understood before it is owned.
A repeatable process for an unrepeatable market.
Discretionary judgement is necessary but insufficient. Systematic process delivers consistency, removes behavioural drift, scales across markets, and — most importantly — makes risk explicit and visible.
Every decision is reproducible. Every position has a documented rationale.
Risk is sized, not guessed. Drawdowns are budgeted before they occur.
A research framework that works across markets, instruments and time horizons.
Selected papers from the desk.
The Empirical Record of Systematic Strategies (1990–2024)
A consolidated review of out-of-sample evidence for the canonical systematic premia — trend, carry, value, momentum, quality, low-volatility — across asset classes and decades.
Regime-Aware Volatility Targeting: An Adaptive Framework
A study of dynamic volatility-targeting estimators that adjust to macro regimes and market microstructure conditions.
Liquidity Fragility in Indian Mid-Caps
Empirical patterns in queue dynamics, order-flow toxicity and impact functions in NSE mid-cap names.
Notes from the research desk.
Trend Following: A Multi-Century Edge Hidden in Plain Sight
Why a simple, century-old idea — buy what is going up, sell what is going down — remains one of the most academically validated and behaviourally durable sources of return in modern markets.
Risk Parity Reconsidered: Beyond the 60/40
A measured look at risk parity twenty years after Bridgewater first popularised it: where the intuition still holds, where the criticism is fair, and how institutional investors are using it today.
Factor Investing in 2025: Value, Momentum, Quality, Low-Volatility
A practitioner’s view of where the canonical equity factors stand after a decade of crowding, drawdown and renewal — and how to construct factor exposure that survives.
Monthly intelligence, written for serious investors.
Quant research, market structure notes and macro framing. No noise.
Talk to our research team.
For institutional mandates, custom research engagements and quant collaboration enquiries. We respond within one business day.