empiricalevidenceonsecurityreturns(编辑修改稿)

empiricalevidenceonsecurityreturns(编辑修改稿)内容摘要：

(small, medium, and big。 or S, M, B) and three booktomarket groups (high, medium, and low。 or H, M, L). The nine portfolios thus formed are labeled in the following matrix。 for example, the S/M portfolio is prised of stocks in the smallest third of firms and the middle third of booktomarket ratio.For each of these nine portfolios, Davis, Fama, and French estimate Equation as a firstpass regression over the 816 months between 1929 and 1997 by using the regression model Table presents some of their results. Notice that the intercepts of the regressions (the estimates of ai for each portfolio) are in fact small and generally (except for the S/L portfolio) statistically insignificant, with tstatistics below 2. The large Rsquare statistics, all in excess of .91, show that returns are well explained by the threefactor portfolios, and the large tstatistics on the size and value loadings show that these factors contribute significantly to explanatory power.How should we interpret these tests of the threefactor model and, more generally, the association of the FamaFrench factors with average returns? One possibility is that size and relative value (as measured by the B/M ratio) proxy for risks not fully captured by the CAPM beta. This explanation is consistent with the APT in that it implies that size and value are priced risk factors. Another explanation attributes these premiums to some sort of investor irrationality or behavioral biases.p. 421Table Threefactor regressions for portfolios formed from sorts on size and booktomarket ratio (B/M)Source: James L. Davis, Eugene F. Fama, and Kenneth R. French, “Characteristics, Covariances, and Average Returns, 1929 to 1997,” Journal of Finance 55, no. 1 (2000), p. 396. Reprinted by the permission of the publisher, Blackwell Publishing, Inc.RiskBased InterpretationsLiew and Vassalou17 show that returns on style portfolios (HML or SMB) seem to predict GDP growth, and thus may in fact capture some aspects of business cycle risk. Each bar in Figure is the average difference in the return on the HML or SMB portfolio in years before good GDP growth versus in years with poor GDP growth. Positive values mean the portfolio does better in years prior to good macroeconomic performance. The predominance of positive values leads them to conclude that the returns on the HML and SMB portfolios are positively related to future growth in the macroeconomy, and so may be proxies for business cycle risk. Thus, at least part of the size and value premiums may reflect rational rewards for greater risk exposure.Petkova and Zhang18 also try to tie the average return premium on value portfolios to risk premiums. Their approach uses a conditional CAPM. In the conventional CAPM, we treat both the market risk premium and firm betas as given parameters. In contrast, as we noted earlier in the chapter, the conditional CAPM allows both of these terms to vary over time, and possibly to covary. If a stock39。 s beta is high when the market risk premium is high, this positive association leads to a “synergy” in its risk premium, which is the product of its beta and market risk premium.What might lead to such an association between beta and the market risk premium? Zhang19 focuses on irreversible investments. He notes that firms classified as value firms (with high booktomarket ratios) on average will have greater amounts of tangible capital. Investment irreversibility puts such firms more at risk for economic downturns because in a severe recession, they will suffer from excess capacity from assets already in place. (In contrast, growth firms are better able to deal with a downturn by deferring investment plans.) The greater exposure of high booktomarket firms to recessions will result in higher downmarket betas. Moreover, some evidence suggests that the market risk premium also is higher in down markets, when investors are feeling more economic pressure and anxiety. The bination of these two factors might impart a positive correlation between the beta of high B/M firms and the market risk premium.p. 422Figure Difference in return to factor portfolios in year prior to aboveaverage versus belowaverage GDP growth. Both SMB and HML portfolio returns tend to be higher in years preceding better GDP growth.Source: J. Liew and M. Vassalou, “Can BooktoMarket, Size and Momentum Be Risk Factors That Predict Economic Growth?” Journal of Financial Economics 57 (2000), pp. 221–45. 169。 2000 with permission from Elsevier Science. To quantify these notions, Petkova and Zhang attempt to fit both beta and the market risk premium to a set of “state variables,” that is, variables that summarize the state of the economy. These are:DIV = Market dividend yield.DEFLT = Default spread on corporate bonds (Baa – Aaa rates).TERM = Term structure spread (10year–1year Treasury rates).TB = 1month Tbill rate.They estimate a firstpass regression, but first substitute these state variables for beta as follows:p. 423Figure HML beta in different economic states. The beta of the HML portfolio is higher when the market risk premium is higher.Source: Ralitsa Petkova and Lu Zhang, “Is Value Riskier than Growth?” Journal of Financial Economics 78 (2005), pp. 187–202. 169。 2005 with permission from Elsevier Science. The strategy is to estimate parameters b0 through b4 and then fit beta using the parameter estimates and the values at each date of the four state variables. In this way, they can estimate beta in each period.Similarly, one can estimate the determinants of a timevarying market risk premium, using the same set of state variables:We can estimate the expected market risk premium for each period using the regression parameter estimates and the values of the state variables for that period. The fitted value from this regression is the estimate of the market risk pr。