Research Doesn’t Tell Us
June 14, 2011
The 2011 paper
Fama and French’s 2011 paper, rather disappointingly, does not attempt to explain why the returns of any stock should depend on its degree of “smallness” and/or “value-ness.” Instead, it is a continuation of the exercise of running data regressions.
Fama and French have access to plenty of data. They use monthly returns data for 23 countries from November 1990 to January 2011, grouping the country data into four major regions – North America, Japan, Asia Pacific, and Europe – and aggregating it to form a global region. They have company size and book-to-market value ratios for all the stocks in their database too, allowing them to divide the stocks for each region into size and value/growth categories.
Having divided the stocks into value and size categories for each region, they construct monthly returns series intended to represent the “size” and “value” components of regional returns. This construction involves a series of rather arbitrary operations. Like the regressions in their 1992 and 1993 papers, these are, say Fama and French, “examples of empirical asset-pricing models; that is, they try to capture the cross-section of expected returns without specifying the underlying economic model that governs asset pricing.” In other words, it’s an exercise in running regressions, not in explaining their results.
One of the objectives of this paper is to see how size/value characteristics affect stock returns within each region, and another is to see how much each region’s returns can be related to global size/value returns.
To explore this question, Fama and French constructed 25 stock portfolios in each region, and regressed them against the three factors: market returns, value stock returns, and small stock returns. If the resulting regression line passes through (or near) the origin of the graph, that means the three factors explain all of the returns, with no residual. In Fama and French’s language, “If we find a set of explanatory portfolios that spans the MV [mean-variance] tangency portfolio, we capture the cross-section of expected returns, whatever the underlying model generating asset prices.” Note the final clause.
The result was that the intercept got pretty close to zero for each region (though not at a high level of statistical significance), especially if you left out microcaps. Microcaps exhibited an exaggerated value effect – their returns increased substantially with value-ness even after the value factor and other factors common to all stocks had been removed. Fama and French did not find as good a fit when they regressed regional returns against global market, size and value factors – a result they interpret as meaning that the regional markets are not globally integrated.
The momentum effect
Fama and French added to this paper a factor that does not appear in their earlier papers: the momentum factor. They made this addition because of the relatively recent observation that stocks have tended to perform better in the subsequent month or year if their previous year’s return outperformed the market.
Fama and French evidently think their work on the momentum factor is important, because in the working paper version I downloaded they included a comment appealing to professional readers of the draft version: “***This is important. Is there a way to give it more emphasis?”
Fama and French’s data exhibit the momentum effect, as have other studies, except in Japan. Adding momentum as a fourth factor creates a better fit to returns, in some regions.
The bottom line
The study’s upshot, ultimately, is something of a dog’s breakfast of conclusions and non-conclusions. I invite anyone with enough interest in this topic to have read this far to view the complete set in the Summary and Conclusions section on pages 21-23 of Fama and French’s paper itself. Perhaps most notable – notwithstanding the extra-strength microcap value effect already mentioned – is a tendency they identify for both the value and momentum effects to exhibit themselves most strongly in smaller stocks, and least strongly in large stocks (with exceptions for Japan). This is perhaps not surprising, since larger stocks are subjected to more market scrutiny and analysis.
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