• What About the Data? The Fama and French (1992) study has itself been challenged. The study's claims most attacked are these: that beta has no role for explaining cross-sectional variation in returns, that size has an important role, and that the book-to-market equity ratio has an important role. The studies responding to the Fama and French challenge generally take a closer look at the data used in that study. Kothari, Shahken, and Sloan (1995) argue that Fama and French's (1992) findings depend critically on how one interprets their statistical tests. Kothari, Shanken, and Sloan focus on Fama and French's estimates for the coefficient on beta [gamma1 in equation (15)], which have high standard errors and therefore imply that a wide range of economically plausible risk premiums cannot be rejected statistically. For example, if the estimate of gamma1 is 0.24 percent per month with a standard error of 0.23 percent, then 0 and 50 basis points per month are both statistically plausible.[7] This view, that the data are too noisy to invalidate the CAPM, is supported by Amihud, Christensen, and Mendelson (1992) and Black (1993). In fact, Amihud, Christensen, and Mendelson (1992) find that when a more efficient statistical method is used, the estimated relation between average return and beta is positive and significant. Black (1993) suggests that the size effect noted by Banz (1981) could simply be a sample period effect: the size effect is observed in some periods and not in others. To make his point, Black uses some findings of Fama and French (1992). They find that their estimate of gama1 in equation (16) is not significantly different from zero for the 1981-90 period. That is, size does not appear to have any power to explain cross-sectional variation in average returns for the period after the Banz (1981) paper was published. This point is also evident in our data in Table 1. In the 1981-91 subperiod, the return on small-firm stocks was 13.3 percent whereas that on the S& 500 stocks was 15.7 percent. One aspect of Fama and French's (1992) result is troubling. Although their point estimate for the coefficient on beta (gamma1) for the 1981-90 sample is statistically significant, it is negative rather than positive, as the CAPM predicts risk premiums to be. This is evidence against the CAPM, but also evidence in favor of the view that the size effect may be spurious and period-specific. Even if there is a size effect, however, there is still a question about its importance given the relatively small value of small finns, as a group, used in these studies. Jagannathan and Wang (1993) report the average market value of firms in each of 100 groups. Finns in the largest 40 percent of the groups account for more than 90 percent of the market value of all stocks on the NYSE and AMEX. Thus, for a large enough collection of assets, the CAPM may still be empirically valid. Another variable that Fama and French (1992) find to be important for explaining cross-sectional variation in returns is the ratio of book-to-market equity. However, Kothari, Shanken, and Sloan (1995) point to another problem with the data (from Compustat) used by Fama and French (1992).[8] The problem is the treatment of firms that are added to the data set and then their data are back-filled by Compustat. Firms that had a high ratio of book-to-market equity early in the sample were less likely to survive and less likely to be included by Compustat. Those that did survive and were added later show high returns. Thus, the procedure has a potential bias. Breen and Korajczyk (1993) follow up on this conjecture by using a Compustat sample that has the same set of firms for all years; no back-filled data are used. They find that the effect of the book-to-market equity ratio is much weaker in these data than that reported by Fama and French (1992).[9] | 
发表于 2005-3-3 13:59
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