The value factor: why underpriced assets have historically outperformed
The value factor captures the tendency of assets that trade at a discount relative to their fundamentals to outperform more expensive peers over time. Fama and French (1992), in The Cross-Section of Expected Stock Returns, documented that high book-to-market stocks outperformed low book-to-market stocks in US equity data going back to 1963—establishing value as one of the most studied premia in academic finance.
What the value factor is
Value investing in its factor form is not about qualitative judgement—it is a systematic process of ranking assets by price-to-fundamentals ratios and overweighting those that appear cheap. The most common metrics are the price-to-book ratio, price-to-earnings ratio, and enterprise value to earnings before interest, taxes, depreciation, and amortisation (EV/EBITDA). An asset with a low P/E or P/B relative to peers or its own history scores highly on the value factor.
The rationale is that markets systematically overreact to recent performance, pushing glamour stocks—those with high recent earnings growth—to excessive valuations while depressing the prices of out-of-favour or distressed companies below their intrinsic value. A disciplined value strategy buys the latter and avoids the former, exploiting what the behavioural explanation calls overreaction and extrapolation.
How the value factor works
A systematic value strategy ranks the investable universe by one or more valuation metrics, forms a portfolio tilted toward high-scoring assets, and rebalances periodically. The choice of metric matters: P/B, P/E, and EV/EBITDA do not always agree on which assets are cheap. Implementations using multiple valuation metrics tend to be more robust than those relying on a single ratio.
Asness, Moskowitz, and Pedersen (2013), in Value and Momentum Everywhere, documented value premia across equities, bonds, currencies, and commodity markets—not only in equities. They also showed that value and momentum are negatively correlated: combining both factors in a portfolio produces better risk-adjusted properties than either achieves alone.
What the evidence shows
Fama and French (1992, 1993) established the value premium in US equities and extended it to international markets. Their three-factor model embedded value alongside market and size factors. Subsequent research confirmed the premium across decades and geographies, though its magnitude varies by market and period.
The value premium's extended underperformance from approximately 2007 to 2020 is the most significant challenge to a straightforward interpretation of the evidence. During this period, growth stocks—particularly in the technology sector—substantially outperformed value by conventional metrics, representing the longest sustained value drawdown in the historical record. Whether this represents a structural change or an extended cyclical drawdown within a long-run premium remains actively debated.
Limitations and trade-offs
A factor that underperforms for 13 years is operationally very difficult to maintain discipline around. Few investors held a value tilt through the entire 2007–2020 drawdown without reducing exposure. Tolerance for extended underperformance is a prerequisite for capturing a factor premium; most investors find this tolerance is lower in practice than in theory.
Value concentration is a structural risk. A value tilt tends to cluster in sectors such as financials, energy, and industrials, leaving the portfolio exposed to sector-specific downturns. The 2008 financial crisis hit value-heavy portfolios particularly hard.
The choice of valuation metric is not neutral. A strategy using book-to-market behaves differently from one using earnings yield or EV/EBITDA, especially in technology-heavy markets where book value has become a poor proxy for economic value as intangible assets have grown in importance. Selecting the metric with the best historical performance is a form of data mining that may not translate forward.
The value factor in pfolio
pfolio's systematic strategy does not implement a value factor tilt. The portfolio construction methodology centres on momentum signals applied across asset classes. Investors who want to understand how their holdings relate to value metrics can use pfolio Insights to track performance by asset class and evaluate holdings against their own criteria. The how we build portfolios help article explains how pfolio selects and weights assets.
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