In the US, factor-based and systematic strategies manage over $1.5 trillion in smart beta ETFs alone, with trillions more in institutional mandates. In India, the number is close to zero. This gap has nothing to do with high-frequency trading — and everything to do with how ordinary equity portfolios are built.

$1.56T Global smart beta ETF assets (Feb 2024)

$142B BlackRock’s factor-based strategies alone

<1% India’s active equity AUM in systematic factor strategies

 

First, Let’s Be Clear About What We’re Not Talking About

When most people hear “quantitative investing,” they picture high-frequency trading: algorithms executing thousands of trades per second, exploiting microsecond price discrepancies, competing on server proximity to exchanges. Firms like Renaissance Technologies’ Medallion Fund, Citadel Securities, and Jump Trading operate in that world. It is a legitimate and fascinating domain — but it has almost nothing to do with what Grey Sky Capital does, or what most investors should care about.

High-frequency trading (HFT) and factor-based systematic investing are as different as Formula 1 racing and building a reliable car for a 20-year road trip. HFT is about speed, capacity constraints, and exotic infrastructure. Factor investing is about disciplined portfolio construction, evidence-based stock selection, and patient compounding. They share the word “quantitative.” That is where the similarity ends.

 

This article is about the second kind: systematic, factor-based, long-only equity investing — the kind that manages trillions of dollars in American retirement accounts, pension funds, and wealth portfolios. The kind that selects stocks based on measurable characteristics like value, momentum, quality, and low volatility. The kind that has quietly become the dominant way serious capital is allocated in the US. And the kind that barely exists in India.

What Factor-Based Systematic Investing Actually Is

At its core, factor investing is built on a simple insight backed by decades of academic research: a small number of measurable stock characteristics — called factors — explain the vast majority of long-term equity returns across every market studied.

A systematic factor strategy does three things differently from a traditional discretionary fund manager. First, it defines its investment criteria in advance using quantifiable rules, not subjective judgement. Second, it applies those rules consistently across a broad universe of stocks — hundreds or thousands, not 15–25 “high-conviction” picks. Third, it rebalances methodically based on changing data, not based on how the fund manager is feeling about the market.

Factor	What It Measures	Why It Works	How It’s Applied
Value	Cheap stocks vs expensive ones	Mean reversion; market overprices growth	Overweight low P/E, P/B, EV/EBITDA stocks
Momentum	Recent winners vs recent losers	Behavioral: herding, underreaction	Overweight stocks with strong 6–12 month returns
Quality	Profitable, stable, well-managed firms	Durable businesses compound better	Overweight high ROE, low debt, stable earnings
Low Volatility	Less volatile stocks	Lottery effect: investors overpay for risk	Overweight stocks with lower historical volatility
Size	Smaller companies vs larger ones	Compensation for illiquidity and risk	Tilt toward mid and small capitalisation

 

The critical point: these are not exotic, high-speed strategies. A factor-based portfolio typically holds stocks for months or quarters, trades infrequently, and can be implemented in a standard PMS or long-only fund structure. No co-located servers. No microsecond execution. No leverage. Just a more disciplined, evidence-based way of selecting and weighting equities.

How Factor Investing Conquered America

The factor revolution in the US did not come from hedge funds. It came from academic research that was systematically commercialised into accessible investment products over three decades.

1992		Fama and French publish the three-factor model (market, size, value), showing that most active manager returns are explained by systematic factor exposures — not stock-picking skill.
1997		Dimensional Fund Advisors (DFA), founded on Fama’s research, reaches $30 billion by offering systematic factor-tilted funds to institutional investors and advisors.
1998		AQR Capital Management founded by Cliff Asness. Begins packaging academic factor research into investable long-only and long-short products for institutions.
2000s		Carhart four-factor model (adding momentum) becomes the standard for performance attribution. Fund managers can no longer hide factor exposure behind narratives.
2006		BlackRock begins building its factor investing platform. Will grow to over $142 billion in factor-based strategies, making it one of the largest in the world.
2013		Smart beta ETFs cross $250 billion globally. Vanguard, iShares, and State Street launch low-cost factor ETFs accessible to any investor.
2019		Smart beta equity ETFs and mutual funds reach approximately $5 trillion in global AUM, representing nearly half of all equity fund assets in some estimates.
2024		Smart beta ETFs alone reach $1.56 trillion globally. AQR manages ~$142 billion. Factor investing is no longer alternative — it is the mainstream.
	An AQR study found that 71% of systematic equity managers generated positive alpha after controlling for factor exposures and market conditions, compared to just 41% of discretionary managers over the same period. The edge is not intelligence. It is process.

The Scale of What India Is Missing

The factor investing ecosystem in the US is not a niche. It is an industry within the industry:

Firm / Category	Factor-Based AUM	What They Do
BlackRock Factor Strategies	~$142 bn	iShares smart beta ETFs; institutional factor mandates
AQR Capital Management	~$142 bn	Multi-factor systematic equity, long-only and long-short
Dimensional Fund Advisors	~$700+ bn firmwide	Academic factor-based equity; value, size, profitability tilts
Vanguard Factor ETFs	~$100+ bn in factor suite	Low-cost factor ETFs: value, momentum, quality, min vol
Avantis Investors (Am. Century)	~$50+ billion	Systematic value and profitability; DFA lineage
Global Smart Beta ETFs (total)	$1.56 trillion	1,330+ products across 38 countries
India: All systematic factor PMS/AIF	< ₹2,000 crore	Handful of quant PMS providers

 

BlackRock’s factor investing division alone — one department within one firm — manages more capital systematically than the entire Indian PMS industry manages in total across all strategies combined. This is not a small gap. It is an entirely different era of asset management.

Why This Matters More Than HFT Headlines

The media fascination with high-frequency trading and hedge fund wizardry obscures a far more important story: the quiet, unglamorous revolution in how ordinary equity portfolios are constructed.

Consider what has happened in the US over the past two decades. The average American investor saving for retirement now has access to multi-factor equity funds that charge 10–30 basis points annually. These funds systematically tilt toward value, quality, momentum, and low volatility — the same factors that explain most of the outperformance historically attributed to star stock pickers. The result is that the “alpha” that active managers once sold at 1–2% fees has been largely converted into “beta” accessible at a fraction of the cost.

High-Frequency Trading (Not what we do) • Holds positions for seconds to milliseconds • Requires co-located servers, exotic hardware • Capacity-constrained: limited to billions • Exploits market microstructure, not fundamentals • Irrelevant to long-term wealth building

Factor-Based Systematic Investing (What we do) • Holds positions for months to quarters • Requires good data and disciplined process • Highly scalable: manages trillions globally • Exploits evidence-based return drivers • Directly applicable to PMS/long-only portfolios

 

Where India Stands: Pioneers in a Pre-Revolution Market

India’s factor-based investing landscape is not entirely empty. A handful of firms have been building genuine systematic strategies:

Estee Advisors, founded in 2008, was among the earliest to bring algorithmic and quantitative approaches to Indian equity management, with its Long Alpha multi-factor PMS. Prabhudas Lilladher’s Quantifi arm launched the AQUA strategy, which applies dynamic factor rotation across market regimes, and has crossed ₹400 crore in AUM. Wright Research offers multi-factor quantitative PMS. And a new generation of factor-native firms — including Grey Sky Capital — is entering the market with systematic approaches built on the same academic foundations that transformed American investing.

But the total assets managed systematically in India remain a rounding error. The vast majority of India’s ₹33+ lakh crore in PMS assets is still managed the old-fashioned way: one fund manager, their conviction, and a thesis built on company visits and gut feeling.

Why the Gap Exists: Structural Barriers

1. The Academic-to-Product Pipeline Is Missing

In the US, the path from academic factor research to investable product is well-established. Fama and French published their research at the University of Chicago. Within years, DFA was commercializing it. AQR was founded by academics who built a bridge between the university and the portfolio. BlackRock hired Columbia’s Andrew Ang to build its factor platform.

In India, this pipeline barely exists. Indian business schools produce excellent research, but the institutional infrastructure to convert academic insights into systematic investment products is nascent. The IIMs and ISI are not feeding a factor investing ecosystem the way Chicago, Wharton, and MIT feed the American one.

2. The Star Manager Culture

Indian HNI investors have been conditioned by decades of personality-driven investing. They want to know who is managing their money, what their thesis is, and why they are bullish on a particular stock. A systematic strategy that says “our models overweight stocks scoring highly on a composite of value, quality, and momentum metrics” does not satisfy the same emotional need as “I visited the factory and met the promoter.”

This is not just an investor education problem. It is a distribution problem. The PMS distribution ecosystem — wealth managers, relationship managers, IFAs — is built to sell narratives, not processes. A multi-factor systematic strategy is harder to pitch over lunch than a star manager’s latest conviction pick.

3. Data Infrastructure Gaps

US factor investing runs on decades of clean, point-in-time, survivorship-bias-free data. CRSP, Compustat, and FactSet provide institutional-grade datasets that have been refined for decades. India’s financial data ecosystem is improving but remains fragmented. Historical corporate action adjustments are inconsistent. Point-in-time fundamental data — essential for avoiding look-ahead bias in backtests — is difficult to source. Building a factor model in India that is genuinely robust requires significantly more data engineering than in the US.

4. Regulatory Friction

SEBI’s PMS regulations were designed for discretionary portfolio management. While a long-only systematic strategy fits comfortably within the PMS framework, certain aspects — performance reporting standards, the emphasis on individual stock rationale, and limited derivative access for hedging — create friction that does not exist for traditional discretionary managers. The new Specialized Investment Fund (SIF) category announced in 2024 may begin to address some of these gaps.

❌ Why India Lags • No academic-to-product pipeline for factor research • Star manager culture deeply embedded in distribution • Fragmented data infrastructure for backtesting • Regulatory framework designed for discretionary PMS • Investor education on systematic approaches is minimal

✅ Why the Gap Will Close • Computational costs have collapsed (cloud, open-source) • NSE/BSE data quality improving rapidly • New generation of factor-native founders returning to India • 70–80% active fund underperformance (SPIVA) is undeniable • SEBI’s SIF category signals openness to innovation

 

Why the Gap Will Close — and Faster Than You Think

Every structural barrier listed above is weakening simultaneously.

The technology barrier is gone. Building a multi-factor equity model in 2025 requires a laptop, Python, and a few thousand rupees a month in cloud computing and data subscriptions. The infrastructure that once required a team of 50 engineers and millions of dollars is now accessible to a three-person team operating from anywhere in India.

The data gap is closing. NSE’s data offerings have expanded significantly. New providers are building India-specific point-in-time databases. The Reserve Bank’s data portal, corporate filing digitisation, and GST data trails are creating signal sources that did not exist five years ago.

The talent pipeline is reversing. Indian quant professionals who built careers at AQR, BlackRock, DFA, and Goldman Sachs are returning to India, bringing world-class factor research expertise. They know how systematic portfolios are built at scale because they built them.

And most importantly, the evidence is becoming impossible to ignore. When 70–80% of active Indian fund managers underperform their benchmarks over five years — a number consistent with the SPIVA India Scorecard — and when global evidence shows that systematic factor strategies deliver comparable or superior returns at a fraction of the cost, the case for change becomes self-evident.

What This Means for Indian Investors

If you are investing ₹50 lakh or more in a PMS today, you are choosing between two eras of asset management. The old era: a single fund manager, their conviction, and a narrative. The new era: a disciplined process, evidence-based factor selection, and systematic portfolio construction. In the US, the new era won. The only question in India is timing.

 

The investors who allocated early to factor-based strategies in the US — the pension funds that backed AQR in the early 2000s, the advisors who adopted DFA over actively managed funds — captured the structural advantages that come from being ahead of an industry transition: lower fees, better diversification, more consistent risk-adjusted returns.

That same window is open in India today. Factor investing in Indian equities is not speculative. The same factors that work globally — value, momentum, quality, low volatility — have robust evidence in Indian markets. What is missing is not the evidence. It is the product ecosystem to deliver it.

At Grey Sky Capital, we are building that ecosystem. Our Smart Core strategy applies multi-factor systematic investing to Indian equities, using the same academic foundations that power trillions in global assets. We hold stocks for months, not milliseconds. We select based on evidence, not anecdotes. We rebalance based on data, not conviction.

The gap between India’s <1% and America’s multi-trillion-dollar factor investing industry will close. The question for Indian investors is whether they will be early adopters, or whether they will wait until it is obvious — and the early-mover advantage is gone.

 

Disclaimer

This article is for informational and educational purposes only. It does not constitute investment advice, a recommendation, or an offer to buy or sell any securities. Past performance of any strategy, including quantitative strategies, is not indicative of future results. All investments carry risk, including the risk of loss of principal. Grey Sky Capital Private Limited is a SEBI-registered Portfolio Manager (Registration No. INP000009694). Investors are advised to consult their financial advisor before making investment decisions. The views expressed are personal opinions of the author and do not necessarily represent the views of Grey Sky Capital.

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