What is the economic explanation for the roles of size and book‐to‐market equity in average returns? Table 2.Results for Fama-MacBeth cross-sectional regressions using the excess returns of 25 portfolios sorted by size and book-to-market. We have examined the monthly slopes from the FM regressions in Table VI for evidence of a January seasonal in the relation between book‐to‐market equity and average return. ME In contrast, the average slope on β for 1966–1990 is close to We do not include the accounting variables in the tests because of the strong selection bias (toward successful firms) in the COMPUSTAT data prior to 1962.   is a measure of book leverage. Ian D. Gow, Gaizka Ormazabal and Daniel J. Taylor, Published By: American Accounting Association, Access everything in the JPASS collection, Download up to 10 article PDFs to save and keep, Download up to 120 article PDFs to save and keep. − , leverage, and book‐to‐market equity in the cross‐section of average returns on NYSE, AMEX, and NASDAQ stocks. and you may need to create a new Wiley Online Library account. ( We exclude financial firms because the high leverage that is normal for these firms probably does not have the same meaning as for nonfinancial firms, where high leverage more likely indicates distress. / Their overreaction story predicts that 3‐year losers have strong post‐ranking returns relative to 3‐year winners. (See the tables for details.). The message from the average FM slopes for 1963–1990 (Table III) is that size on average has a negative premium in the cross‐section of stock returns, book‐to‐market equity has a positive premium, and the average premium for market β is essentially 0. E , also has a strong role in explaining the cross‐section of average returns on Japanese stocks. , can also be interpreted as an involuntary leverage effect, which is captured by the difference between Thus, if there is a role for β in average returns, it is likely to be found in a multi‐factor model that transforms the flat simple relation between average return and β into a positively sloped conditional relation. ) + + Setting β breakpoints with stocks that satisfy our COMPUSTAT‐CRSP data requirements guarantees that there are firms in each of the 100 size‐β portfolios. This item is part of JSTOR collection Three other methods We use a firm's market equity at the end of December of year A worldwide / Average Return is the time‐series average of the monthly portfolio returns for 1941–1990, in percent. Dissecting Characteristics Nonparametrically, https://doi.org/10.1111/j.1540-6261.1992.tb04398.x, Portfolios are formed yearly. The portfolios are formed at the end of June each year and their equal‐weighted returns are calculated for the next 12 months. The 1963–1990 relation between At the end of each year The opposite roles of market leverage and book leverage in average returns are captured well by book‐to‐market equity. Number of times cited according to CrossRef: Recent Applications of Financial Risk Modelling and Portfolio Management. ( is the relative distress factor of Chan and Chen (1991). /   Asset Pricing with Prof. John H. Cochrane PART II. = BE / Appendix Table AI shows that using sum βs produces large increases in the βs of the smallest ME portfolios and small declines in the βs of the largest ME portfolios. Like the overall period, the subperiods do not offer much hope that the average premium for β is economically important. In this section we show that there is also a strong cross‐sectional relation between average returns and book‐to‐market equity. In multivariate tests, the negative relation between size and average return is robust to the inclusion of other variables. E Return Predictability in Firms with Complex Ownership Network. This book‐to‐market relation is stronger than the size effect, which produces a t‐statistic of −2.58 in the regressions of returns on In(ME) alone. 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, For these size portfolios, there is a strong positive relation between average return and β. / t P For example, if there is a general fall in stock prices during the year, ratios measured early in the year will tend to be lower than ratios measured later. Simple tests do not confirm that the size and book‐to‐market effects in average returns are due to market overreaction, at least of the type posited by DeBondt and Thaler (1985). BE Stocks are assigned the post‐ranking (sum)β of the size portfolio they are in at the end of year firms are persistently strong performers, while the economic performance of high BE ME NYSE, AMEX, and NASDAQ stocks that have the required CRSP‐COMPUSTAT data are then allocated to 10 size portfolios based on the NYSE breakpoints. and In In short, our tests do not support the most basic prediction of the SLB model, that average stock returns are positively related to market βs. The FM regressions in Table AIII formalize the roles of size and β in NYSE average returns for 1941–1990. firms have low earnings on assets relative to low Applications of the monthly equal‐weighted portfolio returns ( in percent close in absolute value ). )..... Not explain why β has no explanatory power, it increases the risk captured by BE ME! 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