Value Factor Strategy

The pioneering paper that first documented the value premium with rigorous empirical analysis. Using a comprehensive dataset of U.S. stocks, Rosenberg and colleagues found that stocks with high book-to-price ratios significantly outperformed those with low ratios, even after controlling for risk. The magnitude of the effect was economically significant—too large to be explained by transaction costs or data mining. This paper directly challenged the efficient market hypothesis, suggesting that fundamental analysis could identify mispriced securities. With over 2,100 academic citations, it laid the groundwork for decades of value investing research.

The landmark paper that transformed how we think about stock returns. Analyzing all NYSE, AMEX, and NASDAQ stocks from 1963-1990, Fama and French delivered a stunning finding: size and book-to-market ratio explain cross-sectional return variation far better than beta. The CAPM's market beta showed virtually no explanatory power once these factors were included. High B/M stocks earned ~0.5% per month more than low B/M stocks. The paper sparked intense debate—was this a risk premium or market inefficiency? Either way, it established value as a fundamental factor that no serious investor could ignore, earning over 15,000 academic citations.

Introduced the revolutionary three-factor model that became the industry standard for performance evaluation. By adding SMB (Small-Minus-Big) and HML (High-Minus-Low book-to-market) to the market factor, the model explains over 90% of diversified portfolio returns—compared to just 70% for the CAPM. The HML factor construction became the canonical way to measure value: go long stocks in the top 30% by B/M, short the bottom 30%. From 1963-1991, HML delivered ~5.2% annual returns. The paper also extended the analysis to bonds, showing that term and default risk factors explain bond returns. This unified framework for stocks and bonds has been cited over 30,000 times.

The definitive behavioral explanation for the value premium. LSV argued that value stocks outperform not because they are riskier, but because investors systematically overreact to past performance. Using 1968-1990 data, they showed that "glamour" stocks (low B/M, high past growth) actually underperform value stocks by 10-11% annually over the subsequent 5 years. Crucially, value stocks don't show higher volatility or beta—they're not riskier in conventional terms. The paper introduced the influential idea that investors naively extrapolate past growth rates, overpaying for growth and underpaying for value. This behavioral bias, not risk, explains the premium.

Proved that value is a global phenomenon, not just a U.S. stock anomaly. AMP documented significant value premiums across eight diverse markets and asset classes: U.S. stocks, U.K. stocks, Europe stocks, Japan stocks, country equity indices, government bonds, currencies, and commodity futures. The correlations across markets suggest common global factors drive value everywhere. A crucial insight: value and momentum are negatively correlated (averaging -0.50), meaning they hedge each other. Combining value and momentum in a portfolio significantly reduces volatility while maintaining returns—a rare "free lunch" in finance. The paper also found that both factors are linked to liquidity risk, performing poorly during liquidity crises.

Extended the seminal three-factor model by adding two new factors: profitability (RMW) and investment (CMA). Firms with higher operating profitability and more conservative investment earn higher returns. The five-factor model explains more of the cross-sectional variation in returns, particularly for small stocks. Interestingly, when profitability and investment factors are included, HML becomes largely redundant—its effect is captured by the other factors. This suggests value stocks outperform because they tend to be profitable firms that invest conservatively, not simply because they are "cheap." The paper sparked debate about whether value is a distinct factor or a proxy for quality. Either way, the five-factor model became the new benchmark for academic research.

A thorough investigation into value's extended underperformance from 2007-2020, when growth dramatically outpaced value. The authors identified three main causes: persistently low interest rates (which favor growth stocks' distant cash flows), improper treatment of intangible assets in book value calculations (R&D expensing understates tech firms' true assets), and extreme relative valuations reaching levels not seen since the dot-com bubble. Importantly, they showed that value's underperformance was due to further cheapening of value spreads, not fundamental failure. As valuations became stretched, they argued the probability of a value rebound increased. The paper also proposed improvements to traditional value metrics, adjusting for intangibles and using enterprise value instead of market cap.

A practical guide to improving the academic HML factor for real-world implementation. Blitz and Hanauer showed that the classic book-to-market ratio can be enhanced through several techniques: using composite value metrics (combining B/M with earnings yield, cash flow yield, and EBITDA/EV), excluding financial stocks which have distorted book values, and applying risk management overlays like volatility targeting. These enhancements add 2-3% annually to the basic HML strategy. The paper also documented that industry-neutral value (comparing stocks only to industry peers) outperforms generic value, avoiding unintended sector bets. For practitioners, this paper provides a roadmap for capturing the value premium more efficiently than simple B/M sorting.