Value investing as a systematic strategy
Stocks with a low price relative to book value historically beat more expensively valued stocks. The value premium is one of the longest-known anomalies, but its existence and size have been contested for years.
Unlike chart reading, this strategy is about figures from the balance sheet, not the price path. The basic idea: stocks that are cheap relative to their book value, so-called value stocks, historically beat highly valued stocks, so-called growth stocks.
This pattern became known through economists Eugene Fama and Kenneth French, who systematically documented it in 1992. They built a factor called HML, short for high minus low, that measures the return gap between expensive and cheap stocks.
Investor John Bogle, founder of Vanguard, expressed doubts about the persistence of this so-called value premium, arguing the result depends heavily on the period examined. That debate remains unsettled to this day.
A more recent development further weakens the classic view: in an expanded model by Fama and French from 2015, which additionally accounts for profitability and investment behavior, the pure valuation factor loses a substantial share of its standalone explanatory power. Cheap stocks, it turns out, are often cheap because they're less profitable, not because the market systematically undervalues them.
Fama and French (1992, 1993) showed that the ratio of book value to market value, alongside company size, explains a substantial share of return differences among US stocks that the Capital Asset Pricing Model doesn't capture. Historically, the HML premium in US data since 1926 is put at roughly three to five percent annually, with considerable variation depending on the period studied.
A risk-based and a behavioral view again face off in explanation. Fama and French themselves argue a high book-to-market ratio signals financial distress and therefore a higher, genuinely existing risk, for which the market pays a premium. Behavioral-economics work instead traces the effect to systematically too-optimistic expectations for growth stocks that later prove unfounded.
Golubov and Konstantinidi (2019) and Jaffe et al. (2019) decompose the valuation factor into a mispricing component and a growth-option component and find that essentially only the mispricing component predicts returns. In Fama and French's five-factor model (2015), which adds profitability and investment behavior as separate factors, HML's standalone contribution shrinks considerably, since part of the historical value premium gets explained by these two additional factors. For practical implementation, that means: a bare screen for a low price-to-book ratio, with no regard for a company's profitability, falls systematically short.
Summary
- Historically, cheaply valued stocks beat expensive stocks on average over long periods.
- Whether this value premium is real and persistent has been debated for years.
- Much of the classic value premium can be explained by profitability and investment behavior.
Did you get it?
What does Fama and French's HML factor measure?
The return gap between stocks with a high and a low ratio of book value to market value.
Which two explanations face off on the value premium?
A risk-based one reading financial distress as a risk signal, and a behavioral one citing overly optimistic expectations for growth stocks.
What changes in Fama and French's five-factor model?
Profitability and investment behavior get added as separate factors, which shrinks the standalone contribution of the pure valuation factor considerably.
Sources and further reading
- Fama, E. F. and French, K. R. (1992), The Cross-Section of Expected Stock Returns, Journal of Finance
- Fama, E. F. and French, K. R. (1993), Common Risk Factors in the Returns on Stocks and Bonds, Journal of Financial Economics
- Fama, E. F. and French, K. R. (2015), A Five-Factor Asset Pricing Model, Journal of Financial Economics
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