E More important, COMPUSTAT data for earlier years have a serious selection bias; the pre‐1962 data are tilted toward big historically successful firms. / t If so, it is not surprising that the variation in β within a size decile is unrelated to average return, or that size dominates β in bivariate tests. E Evaluating Business Performance Using Data Envelopment Analysis and Grey Relational Analysis. A The results to here are easily summarized: Even if our results are consistent with asset‐pricing theory, they are not economically satisfying. In this section we show that there is also a strong cross‐sectional relation between average returns and book‐to‐market equity. Interestingly, there is a reliable simple relation between β and average return during the 1941–1965 period. 1 We can report, however, that our inference that there isn't much relation between β and average return is unchanged when (a) the market proxy is the NYSE EW portfolio, (b) portfolios are formed on just (pre‐ranking) βs, or (c) the order of forming the size‐β portfolios is changed from size then β to β then size. million) and toward stocks with relatively high book‐to‐market ratios (Table IV says that In Table II shows post‐ranking average returns for July 1963 to December 1990 for portfolios formed from one‐dimensional sorts of stocks on size or β. The lower correlation means that bivariate regressions of returns on β and ln(ME) are more likely to distinguish true size effects from true β effects in average returns. It is possible that, by chance, size and book‐to‐market equity happen to describe the cross‐section of average returns in our sample, but they were and are unrelated to expected returns. One possibility is that the variation in β produced by the β sorts of size deciles in just sampling error. Panel A shows our results for value-weighted portfolios. / The average return matrix gives life to the conclusion from the regressions that, controlling for size, book‐to‐market equity captures strong variation in average returns, and controlling for book‐to‐market equity leaves a size effect in average returns. 0.06 / Table VI shows the average FM slopes for two roughly equal subperiods (July 1963–December 1976 and January 1977–December 1990) from two regressions: (a) the cross‐section of stock returns on size, In(ME), and book‐to‐market equity, In Finally, the Similarly, small firms have a long period of poor earnings during the 1980s not shared with big firms. E Table IV shows average returns for July 1963 to December 1990 for portfolios formed on ranked values of book‐to‐market equity Efficiency of multi-factor models for evaluating the yield on financial assets in the Russian stock market. BE JSTOR is part of ITHAKA, a not-for-profit organization helping the academic community use digital technologies to preserve the scholarly record and to advance research and teaching in sustainable ways. BE E The relation between ( help explain the cross‐section of average returns on U.S. stocks in tests that also include size and market β. in the regressions that include ME ME We use the βs of portfolios formed on size and β, and our market is the value‐weighted NYSE portfolio. are about 4 standard errors from 0, and they are close to (within 0.05 of) the average slopes for the whole year. We put little weight on this possibility, especially for book‐to‐market equity. . E P The Accounting Review E / / A high ratio of book equity to market equity (a low stock price relative to book value) says that the market judges the prospects of a firm to be poor relative to firms with low This results in a distress factor in returns that is priced in expected returns. BE Resuscitation of the SLB model requires that a better proxy for the market portfolio (a) overturns our evidence that the simple relation between β and average stock returns is flat and (b) leaves β as the only variable relevant for explaining average returns. E t 2.97 ) Proceedings of the Thirteenth International Conference on Management Science and Engineering Management. P / B. Fama‐MacBeth Regressions Table III shows time‐series averages of the slopes from the month‐by‐month Fama‐MacBeth (FM) regressions of the cross‐section of stock returns on size, β , and the other variables (leverage, E / P , and book‐to‐market equity) used to explain average returns.

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