60 The Journal of Finance critical to allow for variation in SMB and HML slopes when applying (1)and (2)to industries. II.LSV Deciles Lakonishok,Shleifer,and Vishny(LSV 1994)examine the returns on sets of deciles formed from sorts on BE/ME,E/P,C/P,and five-year sales rank.Table II summarizes the excess returns on our versions of these portfolios.The portfolios are formed each year as in LSV using COMPUSTAT accounting data for the fiscal year ending in the current calendar year(see table footnote).We then calculate returns beginning in July of the following year.(LSV start their returns in April.)To reduce the influence of small stocks in these (equal- weight)portfolios,we use only NYSE stocks.(LSV use NYSE and AMEX.)To be included in the tests for a given year,a stock must have data on all the LSV variables.Thus,firms must have COMPUSTAT data on sales for six years before they are included in the return tests.As in LSV,this reduces biases that might arise because COMPUSTAT includes historical data when it adds firms (Banz and Breen (1986),Kothari,Shanken,and Sloan(1995)). Our sorts of NYSE stocks in Table II produce strong positive relations between average return and BE/ME,E/P,or C/P,much like those reported by LSV for NYSE and AMEX firms.Like LSV,we find that past sales growth is negatively related to future return.The estimates of the three-factor regres- sion (2)in Table III show,however,that the three-factor model (1)captures these patterns in average returns.The regression intercepts are consistently small.Despite the strong explanatory power of the regressions(most R2 values are greater than 0.92),the GRS tests never come close to rejecting the hypoth- esis that the three-factor model describes average returns.In terms of both the magnitudes of the intercepts and the GRS tests,the three-factor model does a better job on the LSV deciles than it does on the 25 FF size-BE/ME portfolios. (Compare Tables I and III.) For perspective on why the three-factor model works so well on the LSV portfolios,Table III shows the regression slopes for the C/P deciles.Higher-C/P portfolios produce larger slopes on SMB and especially HML.This pattern in the slopes is also observed for the BE/ME and E/P deciles(not shown).It seems that dividing an accounting variable by stock price produces a characterization of stocks that is related to their loadings on HML.Given the evidence in FF (1995)that loadings on HML proxy for relative distress,we can infer that low BE/ME,E/P,and C/P are typical of strong stocks,while high BE/ME,E/P,and C/P are typical of stocks that are relatively distressed.The patterns in the loadings of the BE/ME,E/P,and C/P deciles on HML,and the high average value of HML(0.46 percent per month,6.33 percent per year)largely explain how the three-factor regressions transform the strong positive relations be- tween average return and these ratios(Table II)into intercepts that are close to0.0. Among the sorts in Table III,the three-factor model has the hardest time with the returns on the sales-rank portfolios.Recall that high sales-rank firms