--- title: "Introduction to Investment Factors | RupeeCase Learn" description: "What Value, Momentum, Quality, Low Volatility and Size factors are, why they generate persistent returns, and how they work in Indian markets." source_url: "https://www.rupeecase.com/learn/path-2/module-2-2-introduction-to-factors" --- Skip to main content [Learn](/learn)›[Path 2: Systematic Investing Fundamentals](/learn/path-2)›Module 2.2 # Introduction to Factors The five proven return drivers that systematic strategies are built on, what each factor is, why it works, and what it looks like in Indian markets. TK Tanmay Kurtkoti Founder & CEO, RupeeCase · QC Alpha ⏱ 16 min read ⟳ Updated 15 Jun 2026 ◆ Intermediate In 1992, Eugene Fama and Kenneth French published a paper that changed academic finance permanently. They showed that the market portfolio alone couldn’t explain stock returns, two other measurable characteristics did most of the work: company size and book-to-market ratio. The CAPM model that had dominated for decades was incomplete. That paper opened a 30-year research programme into what are now called **factors**, measurable stock characteristics that predict returns systematically, across markets, across decades, and across countries. The most important ones have been replicated in Indian markets too. A factor is a measurable characteristic of a stock that has been shown through extensive academic research to systematically predict returns above the market benchmark. Same signal, all stocks, applied consistently over many years. Why factors beat stock picking: the Indian proof 30 Years of research Fama French 1992 onwards 5 Major factors in India Value, Momentum, Quality, Low Vol, Size 4.9 Pct long term premium Nifty 200 Momentum vs Nifty 50 500 Stocks in universe Nifty 500, RupeeCase default NSE Indices SEBI Smart Beta AMFI Factor Funds ## The Fama-French foundation Fama & French (1992), Three-Factor Model Expected Return = Market Risk + Size Premium + Value Premium The original paper showing small-cap stocks and high book-to-market (cheap) stocks earned returns unexplained by market risk alone. The formal beginning of factor investing as an academic discipline. Fama, E. & French, K. (1992). The Cross-Section of Expected Stock Returns. Journal of Finance. Fama & French (2015), Five-Factor Model Expected Return = Market + Size + Value + Profitability + Investment Two decades later: Profitability (companies that earn more consistently) and Investment (companies that invest conservatively) added as additional return predictors. Current academic standard. Fama, E. & French, K. (2015). A Five-Factor Asset Pricing Model. Journal of Financial Economics. [Fama-French Data Library, Factor returns, methodology, data](https://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html) From market beta to 5 factors: the evolution of what matters 1964 CAPM Market beta only 1992 3 factor + Size + Value 1993 Momentum Jegadeesh + Titman 2015 5 factor + Profitability + Investment 2020s Multi factor Blended in Indian ETFs ## The five major factors 💰 Value Cheap stocks outperform expensive ones over time Signal: Low P/B · Low P/E · Low EV/EBITDA Stocks trading at a low price relative to fundamentals, book value, earnings, or cash flow, have historically earned higher returns than expensive glamour stocks. Markets overprice hype and underprice boring, unloved businesses. Mean reversion does the rest. **In India:** Strong value factor returns in Nifty 500, particularly post-corrections when cheap stocks are deeply discounted. PSU banks and commodity stocks periodically appear as deep value plays. NSE tracks this via the Nifty Value 20 Index. 📈 Momentum Recent winners keep winning over 3 to 12 months Signal: 12M-1M trailing price return Stocks that outperformed over the past 6 to 12 months (excluding the most recent month, which tends to reverse) continue to outperform over the next 3 to 12 months. Rationale: markets underreact to positive news, causing gradual price adjustment rather than immediate repricing. **In India:** Momentum is among the strongest factors in NSE data. The Nifty Alpha 50 and Nifty Momentum 30 indices track this. RupeeCase’s strategies are built on cross-sectional momentum across Nifty 500, with strong statistical significance in NSE research papers. ✦ Quality Profitable, low-debt businesses outperform over cycles Signal: High ROE · Low D/E · Stable earnings Companies with high profitability, low financial leverage, and consistent earnings growth tend to compound wealth more reliably than low-quality businesses. The market only partially prices in the value of durable competitive advantages. Linked to Fama-French’s Profitability factor. **In India:** Quality companies like [BAJFINBajaj Finance](https://www.nseindia.com/get-quotes/equity?symbol=BAJFINANCE), [HDFCBKHDFC Bank](https://www.nseindia.com/get-quotes/equity?symbol=HDFCBANK), and [ASIANPTAsian Paints](https://www.nseindia.com/get-quotes/equity?symbol=ASIANPAINT) have consistently rewarded long-term holders. NSE’s Nifty Quality 30 Index tracks this systematically. Powerful in India because corporate governance varies widely across Nifty 500. 🕑 Low Volatility Less volatile stocks deliver better risk-adjusted returns Signal: Low 1-year daily return standard deviation The Low Volatility anomaly is counterintuitive: theory says higher risk = higher return. In practice, lower-volatility stocks have delivered comparable or higher returns with less risk. Rationale: investors overpay for “lottery ticket” volatile stocks and underpay for stable, boring ones. **In India:** FMCG, pharma, and consumer staples like [NESTLNestle India](https://www.nseindia.com/get-quotes/equity?symbol=NESTLEIND) often rank high on Low Volatility. NSE tracks this via the Nifty Low Vol 50 Index. Works well as a complement to Momentum, combining them reduces drawdown significantly. 📊 Size Small-caps earn higher returns than large-caps over time Signal: Low market capitalisation Smaller companies have historically earned higher returns than larger ones, the original Fama-French finding. Rationale: small caps are less covered by analysts, more illiquid, and often mispriced. Investors demand a premium for the extra risk. The size premium is real but lumpy and can disappear for years. **In India:** Significant premium in Nifty Midcap and Smallcap segments. But liquidity constraints matter, many small-cap stocks have insufficient daily volume to deploy meaningful capital without moving the price against you. RupeeCase’s Nifty 500 universe filters for minimum liquidity to address this. Indian factor premium: excess return over Nifty 500 TRI, 2015 to 2025 Momentum (Nifty 200 Mom 30) +4.9 Low Vol (Nifty Alpha Low Vol 30) +3.4 Quality (Nifty Quality 30) -0.6 Value (Nifty 100 Value 20) -2.7 Size (Nifty Midcap 150) +4.2 Annualised excess return vs Nifty 500 TRI, 10 years to 31 Mar 2025. Source: NSE Indices. No factor wins every year. Combining Momentum + Low Vol historically beats every single factor on Sharpe. Why the 5 factors win: the 3 drivers of persistence Behavioural (investor bias)45% Structural (benchmarking, mandates)35% Risk compensation (real risk)20% Approximate split of academic explanations. The behavioural plus structural share is what keeps the premium alive in India. Indian mutual fund managers cannot hold a 30 pct Value sleeve for 3 underperformance years without losing AUM. ## Why factors persist If factors generate excess returns, why doesn’t everyone exploit them until they disappear? Three complementary answers: 1 Risk-based explanations Some factors may represent compensation for real economic risk. Value stocks are often companies in financial stress, they’re cheap because they’re risky. You earn higher returns because you bear real risk of permanent capital loss. 2 Behavioural explanations Some factors persist because of systematic human bias. Momentum exists partly because investors underreact to news, prices adjust slowly. Low Volatility persists because investors overpay for exciting, volatile stocks and underpay for boring stable ones. As long as these biases exist, the premia should persist. 3 Structural/institutional explanations Fund managers benchmark against large-cap indices, they’re evaluated quarterly and can’t hold Value positions that underperform for 2 to 3 years even when the thesis is correct. These structural constraints create persistent pricing inefficiencies that systematic investors exploit. **The honest caveat:** Factor premia are real but not smooth. Value underperformed for a decade before the 2022 rotation. Momentum can crash 30 to 40% in sharp reversals. Size premia disappear in large-cap bull markets. Factors require patience measured in years, not months, which is why combining multiple factors smooths the ride. [NSE Indices, Factor & Strategy Indices (Momentum, Quality, Value, Low Vol)](https://www.niftyindices.com/indices/equity/strategy-indices) ~18% Approximate Momentum factor annual premium above Nifty 500 (10Y NSE data, directional estimate) ~12% Approximate Quality factor annual premium above Nifty 500 (10Y NSE data, directional estimate) ~8% Approximate Value factor annual premium above Nifty 500 (10Y NSE data, directional estimate) ◆ How RupeeCase uses factors Every strategy on **[RupeeCase](https://invest.rupeecase.com)** is built on one or more of these five factors. The NSE Momentum strategy uses cross-sectional momentum across Nifty 500. The factor screener lets you rank all 500 stocks on any combination of signals. **This is the engine under the hood.** Factors live in the terminal Rank all 500 Nifty stocks by Value, Momentum, Quality and more Factor scores updated nightly. Real NSE data. No spreadsheets. [Start free →](https://invest.rupeecase.com/signup) TK | The day factors clicked for me For my first 4 years as a trader I was a pure discretionary stock picker. Terminal in one hand, broker chat in the other, convinced the next Bajaj Finance was one earnings call away. I outperformed Nifty 50 in some years, underperformed in others, mostly noise. In 2018 I sat down with a proper multi factor backtest on Nifty 500, Value + Momentum + Quality, monthly rebalance. The equity curve was not sexy. It did not catch every multibagger. What it did was beat the index on a Sharpe basis in 8 out of 10 calendar years without me doing anything discretionary. That was the moment I stopped arguing with charts and started arguing with signals. Factors are not magic. They are what remains when you take out the ego. Every strategy on RupeeCase is a bet on that same lesson. TK A note from the author Why factors matter more than stock tips The single biggest shift in how I think about markets is moving from “which stock?” to “which characteristic?”. Stock tips are noise. Factor premia are signal backed by decades of global academic research and real return data from Indian markets. When I build a strategy on RupeeCase, I’m not guessing which company will do well. I’m asking: which stocks exhibit the characteristics that have historically predicted outperformance? The research answers that question. My job is to implement it cleanly and stick to it. TK Tanmay Kurtkoti Founder & CEO, RupeeCase · 17 years systematic trading · QC Alpha RC **Put learning into practice.** Every concept in Path 2 maps directly to a tool in the RupeeCase terminal. [Explore terminal →](https://invest.rupeecase.com) Glossary, Module 2.2 FactorA measurable stock characteristic that systematically predicts returns above the market benchmark across time and markets. Value factorStocks cheap relative to fundamentals (low P/B, P/E, EV/EBITDA) tend to outperform expensive stocks over time. Momentum factorStocks that outperformed over the past 12 months (minus last 1 month) tend to continue outperforming over the next 3 to 12 months. Quality factorHigh profitability (ROE), low leverage, and stable earnings predict outperformance over full market cycles. Low Volatility factorStocks with lower price volatility deliver better risk-adjusted returns than high-volatility stocks, opposite of what standard theory predicts. Size factorSmaller-cap stocks earn higher returns than large-caps historically, compensating for illiquidity and lower analyst coverage. Factor premiumExcess return earned by a factor strategy above the market benchmark. E.g. if Nifty returned 14% and your momentum strategy returned 22%, the premium was approximately 8%. #### Sources & further reading * → [Fama-French Data Library, Factor returns, research, methodology](https://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html) * → [NSE Research, Factor Returns in Indian Equity Markets (Working Paper)](https://www.nseindia.com/research/content/NSE_WP_25.pdf) * → [NSE Indices, Strategy & Factor Index Family](https://www.niftyindices.com/indices/equity/strategy-indices) * → Fama, E. & French, K. (1992). *The Cross-Section of Expected Stock Returns*. Journal of Finance. * → Fama, E. & French, K. (2015). *A Five-Factor Asset Pricing Model*. Journal of Financial Economics. * → Jegadeesh, N. & Titman, S. (1993). *Returns to Buying Winners and Selling Losers*. Journal of Finance. ©All content on this page is original work by Tanmay Kurtkoti and QC Alpha Technologies Pvt Ltd. Protected under Indian copyright law. tanmay@rupeecase.com ### Quick check, Module 2.2 0 correct · 0 answered ✓ Module complete! Next module unlocked. 🎉 Module 2.2 complete 3 correct. Continue when ready. 🎓 Spread the knowledge This course is completely free. Help someone learn systematic investing, share it. 📋 Suggested LinkedIn post Just completed Module 2.2 of Tanmay Kurtkoti's free systematic investing course on RupeeCase. Finally understand what investment factors actually are | and why Fama-French research applies to NSE/Nifty 500 stocks. Free at rupeecase.com/learn Copy text Share on X Post on LinkedIn Copy link Research Lab Qualifier Path 2, Module 2 of 5, complete all 5 + path test to unlock [Explore terminal →](https://invest.rupeecase.com) ✅ 2.1 Rules vs Gut→📍 2.2 Factors→2.3 Risk Metrics→2.4 Backtesting→2.5 Build a Strategy [← Previous](module-2-1-why-rules-beat-gut-feeling.html) Previous, Module 2.1 Why Rules Beat Gut Feeling Calculator ### Factor Score Z-Normaliser Multi-factor portfolios need normalised scores so no single factor dominates. The z-score puts every factor on the same scale. Stock raw valueUniverse meanUniverse standard deviationHigher is better?Yes (e.g., ROE, momentum)No (e.g., P/E, debt-to-equity) Quick check, Module 2.2 ## 3 questions. Get 2 right to mark this module complete. 0 of 3 answered ✓ Module complete. Keep going. Up next, Module 2 Risk Metrics That Matter Sharpe ratio, Sortino, max drawdown, CAGR, what each one tells you and what it doesn’t. How to evaluate a strategy honestly. 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