The caPm is Wanted. Dead or Alive TORIo Eugene F Fama: Kenneth R. French The Journal of finance, Vol. 51, No. 5.(Dec, 1996), pp. 1947-1958 Stable url: http://links.jstor.org/sici?sici=0022-1082%028199612%2951903a5%03c1947%03atciwdo%3e2.0.c0%03b2-6 The Journal of finance is currently published by American Finance Association Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/about/terms.htmlJstOr'sTermsandConditionsofUseprovidesinpartthatunlessyou have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at http://wwwjstor.org/journals/afina.html Each copy of any part of a JSTOR transmission must contain the same copy tice that appears on the screen or printed page of such transmission jStOR is an independent not-for-profit organization dedicated to creating and preserving a digital archive of scholarly journals. For more information regarding JSTOR, please contact support@jstor. org http://www」]stor.org Thu mar3005:36:512006
E JJOURNAL OF FINANCE. VOL. LI. NO 5. DECEMBER 1996 The caPm is Wanted Dead or Alive EUGENE F FAMA and Kenneth R. French shanken, and Sloan(1995)claim that &s from annual returns produce positive relation between B and average return than Bs from monthl They also contend that the relation between average return and book-to- market equity(BE/ME)is seriously exaggerated by survivor bias. We argue that urvivor bias does not explain the relation between BE/mE and average return. We also show that annual and monthly Bs produce the same inferences about the B premium. Our main point on the B premium is, however, more basic. It cannot the Capital asset pricing model(CAPM), given the evidence that B alone cannot FAMA AND FRENCH(FF 1992)PRODUCE two negative conclusions about the em- pirical adequacy of the capital asset pricing model(CAPM)of Sharpe(1964) and Lintner(1965): (i)when one allows for variation in CAPM market Bs that is unrelated to size. the ur te relation between B and turn fo 1941-1990 is weak; (ii)B does not suffice to explain average return. Size (market capitalization)captures differences in average stock returns for 1941- 1990 that are missed by B For the post-1962 period where we have book equity data, Be/mE (the ratio of book to market equity) and other variables also help explain average return Kothari, Shanken, and Sloan(KSS 1995) have two main quarrels with these conclusions. First, they claim that using Bs estimated from annual rather than monthly returns produces a stronger positive relation between average return and B. Second, KSS contend that the relation between average return and BE/ME observed by Ff and others is seriously exaggerated by survivor bias in the COMPUStat sample We argue( Section Ii) that survivor bias does not explain the relation be tween BE/mE and average return. We also show(Section III)that annual and monthly Bs produce the same inferences about the presence of a B premium in expected returns. But our main point on the B premium( Section I)is more basic: It cannot save the CaPm, given the evidence that B alone cannot explain expected return I. The Logic of Tests of the CAPM As emphasized by Fama(1976), Roll (1977), and others, the main implication of the CaPM is that in a market equilibrium, the value- weight market port- s Graduate School of Business, University of Chicago(Fama), and Yale School of Management (French). We acknowledge the helpful comments of Josef Lakonishok, Rene Stulz, and a referee 1947
1948 The Journal of finance folio, M, is mean-variance-efficient. The mean-variance-efficiency of M in turn says that: (i) B, the slope in the regression of a securitys return on the market return, is the only risk needed to explain expected return ii) There is positive expected premium for B risk Our main point is that evidence of (ii), a positive relation between B and expected return, is support for the CAPM only if (i)also holds, that is, only if suffices to explain expected return. Confirming Banz(1981), however, and like FF(1992), KSS find that size adds to the explanation of average return provided by B. Moreover, size is no longer the prime embarrassment of the CAPM. Variables that (unlike size)do not seem to be correlated with B(such as earnings/price, cashflow/price, BE/ME, and past sales growth) add even more significantly to the explanation of average return provided by B(Basu (1983), Chan, Hamao, and Lakonishok (1991), FF(1992, 1993, 1996), and Lakonishok, Shleifer, and Vishny(1994)). A The average-return anomalies of the CAPM suggest that, if asset pricing is tional, a multifactor version of Mertons(1973) intertemporal CAPm (ICAPM)or Ross'(1976)arbitrage pricing theory(APT) can provide a better description of average returns. The excess market return of the CAPM is a relevant risk in many multifactor alternatives, like the ICAPM and Connor's (1984)equilibrium version of the APT. Thus, evidence of a positive relation between B and expected return does not favor the CAPm over these alterna The three-factor model in Fama and French(1993, 1994, 1995, 1996)illus- trates our point. The model provides a better description of average returns than the CaPM, and it captures most of the average-return anomalies missed by the CAPM. Because of its strong theoretical standing, the excess market return is one of the three risk-factors in the model, and our tests confirm that it is important. It captures strong common times-series variation in returns, and the market premium is needed to explain the large differences between the average returns on stocks and bills. Moreover, as in the CaPm, the market premium in our multifactor model is just the average return on M in excess of the risk-free rate. Tests on long sample periods say that this premium reliably positive In short, our tests of the CAPm against a multifactor alter native illustrate that a positive p premium does not in itself resuscitate the CAPM, or justify using it in applications KSS are not misled on this basic point. But their focus on the univariate p premium may confuse some of their readers. Indeed, because the CAPM is such a simple and attractive tool, we think that many of our colleagues want to be confused on this point. Otherwise, we cant explain the strong interest in the KSS p tests, given that, like many others(including Amihud, Christensen, and Mendelson(1992)and Jagannathan and Wang( 1996), KSS consistently find that B does not suffice to explain expected return
The capm is Wanted, Dead or Alive 1949 I. Survivor bias and bEme KSS argue that survivor bias in COMPUSTAT data is important in the strong positive relation between average return and book-to-market-equity(BE/me) observed by FF(1992)and others. COMPuStat is more likely to add dis tressed (high-BE/ME) firms that ultimately survive and to miss distressed firms that die. The survivors are likely to have unexpectedly high returns in the turnaround years immediately preceding their inclusion on COMPUStat. Since comPustat typically includes some historical data when it adds firms there can be positive survivor bias in the returns of high-BE/ME firms or COMPUSTAT There are counter arguments. In the most detailed study of the issue, Chan, Jegadeesh, and Lakonishok(1995)conclude that survivor bias cannot explain the strong relations between average return and be/me observed by lakon- ishok, Shleifer, and Vishny(1994)and FF(1992)in tests on the post-1968 and post-1976 periods After 1968, and certainly after 1976, almost all the traded securities on Center for Research in Security Prices(CRSP) that are not on COMPUSTAT are missing for reasons that have nothing to do with survivor bias. Many of the missing firms are closed-end investment companies, REIts ADRs, primes, and scores that produce no accounting information or produce information that is not comparable to that of other firms. Many financial companies are also missing because, judging that their accounting data are different from that of other firms, COMPUSTAT limited its coverage of finan ials for many years. These omissions, which are the result of COMPUSTAT's ex ante policy decisions, are not a source of survivor bias. Finally, some of the securities that seem to be on CrsP but not COMPUSTat in fact appear on both. but with different identifiers There is other evidence that survivor bias cannot explain the relation be tween average return and BE/ME. Lakonishok, Shleifer, and Vishny(1994) find a strong positive relation between average return and BE/ME for the largest 20 percent of NYSE-AMEX stocks on COMPUSTAT, where survivor bias is not an issue. FF(1993) find that the relation between BE/ME and average return is strong for value-weight portfolios of COMPUSTAT stocks formed on BE/E. Since value-weight portfolios give most weight to larger stocks, any survivor bias in these portfolios is probably trivial. In three differ- ent sets of comparisons Table Vil), kss themselves find that the relation between average return and be/me is strong and strikingly similar for value- weight and equal-weight portfolios of COMPUSTAT stocks formed on BE/ME. KSS concede that survivor bias cannot explain the results for value-weight portfolios To support their survivor-bias story, KSS make much of the fact that stocks on CrsP but not COMPUSTAT have lower average returns than stocks on COMPUSTAT. When they risk-adjust returns using a three-factor model like that in FF(1993), however, only the smallest two size deciles of the NYSE AMEX stocks missing from CoMPUSTaT have strong negative abnormal
1950 The ournal of finance returns(Table IV). This suggests that survivor bias is limited to tiny stocks the average market cap of the stocks in the second decile is $13 million, while the average for the first decile is between $3 million and $7 million. The remaining 80 percent of the stocks missing on COMPUSTAT, which account for almost all the combined value of the missing stocks, have three-factor abnormal returns that are close to zero and random in sign. In other words these missing stocks behave like stocks that are on COMPUSTAT. Similarly, Chan, Jegadeesh, and Lakonishok(1995)fill in missing COMPUSTAT book equity(be)data for the largest 20 percent of the NYSE-AMEX firms on CRSP. The survivor-bias story says that the relation between BE/ME and average return should be weak for the firms missing on COMPUSTAT. They find that it is as strong for the missing firms as for the included firms KSS also speculate that the positive relation between book-to-market-equity and average return is the result of data dredging and so is special to the post-1962 COMPUSTAT period Using a hand-collected sample of large firms that is not subject to survivor bias, however, Davis(1994)finds a strong relation between BE/ME and average return in the 1941-1962 period In the end, the KSS survivor-bias story rests on their evidence that there is little relation between average return and BE/E for the rather limited industry portfolios in the S&P Analyst s Handbook. Their results for the S&P industries are strange since FF(1994)document a strong positive relation between average return and BE/ME for value-weight industry portfolios that include all NYSE, AMEX, and Nasdaq stocks on CRSP. (We use COMPUSTaT firms only to estimate industry BE/ME) ksS do not say that the relation between average return and BE/e is entirely the result of survivor bias. They push so hard on the survivor-bias story, however, that serious readers are led to strong conclusions. For example, in the lead article to volume 38 of the Journal of Financial Economics MacKinlay(1995, p 5)concludes, " Their analysis suggests that deviations from the CAPM such as those documented by Fama and French(1993)can be explained by sample selection biases III. Minor points KSS claim that using Bs estimated from annual rather than monthly returns explains why they measure somewhat stronger relations between B and aver age return than FF(1992). They also claim that although the explanatory power of size is statistically reliable, for practical purposes, size adds little to the explanation of average return provided by B. The tests that follow explore A. Portfolios Formed on B Table I summarizes returns for 1928-1993 on B deciles of NYSE stocks. Like KSS, we weight the stocks equally. We form the portfolios in June of each year