The Half-Life Of Smart Beta

October 23, 2013


Like the small-cap effect, the value effect may prove to be smaller than it was when first described by Graham and Dodd or quantified by Fama and French. The Fama-French data set initially covered U.S. stocks between 1926 and 1990, and has been extended through 2011. Up through 1992, value outperformed growth in all segments of the U.S. market. Since 1992, at least for U.S. stocks, the value effect has been confined to the small-cap universe. This makes a good bit of sense. Griffin and Lemmon documented that the book-to-market effect is largest in small firms with low analyst coverage.14 Figure 3 summarizes Fama and French’s results from testing portfolios in various style boxes against each other, highlighting areas where results were statistically significant at the 95 percent level.


If there is a real risk of distress that could lead to default or dilution, small-cap companies are bound to be primary bearers of this risk, since they lack the capitalization buffer of large-caps. Moreover, Griffin and Lemmon, joined by Lai Van Vo, added to this explanation the observation that institutional investors avoid holding and trading stocks with high distress risk, which tend to be small-cap value stocks.15

Putting the pieces together, we find that the disappearance of the value effect in all but the small-cap segment of the market clarifies the risks involved. Since 1992, many investment vehicles have popped up, allowing institutional and individual investors access to value funds or value tilts to their exposures. This increased investor interest has arbitraged away much of the value premium. What remains can be attributed to risk and to market structure: The possibility of default and the illiquidity (caused by avoidance from institutional investors), combined with the informational asymmetries that accompany the lack of analyst coverage, all create risks and costs for investors.

First documented in 1993,16 and then again in 2001,17 by Jegadeesh and Titman, the momentum effect describes the phenomenon that stocks whose prices have been rising in the recent past (usually between three and 12 months ago) are likely to see continued price appreciation compared with those whose returns have been falling during the same time frame.

Many researchers, including Fama and French, Barberis and Thaler, and Jegadeesh and Titman, have posed a behavioral explanation for momentum. They find momentum to be explained by the slowness of investors to fully respond to new information, a slowness they believe to be irrational. According to this explanation, investors take a while to re-value stocks after news breaks, so rising stocks will continue to rise, and falling stocks will continue to fall, until all investors have assimilated and priced-in yesterday’s (or last year’s) news.



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