This paper explores the ability of conditional versions of the CAPM and the consumption CAPM—jointly the (C)CAPM—to explain the cross section of average stock returns. Central to our approach is the use of the log consumption–wealth ratio as a conditioning variable. We demonstrate that such conditional models perform far better than unconditional specifications and about as well as the Fama-French three-factor model on portfolios sorted by size and book-to-market characteristics. The conditional consumption CAPM can account for the difference in returns between low-book-to-market and high-bookto-market portfolios and exhibits little evidence of residual size or book-to-market effects. We are grateful to Eugene Fama and Kenneth French for graciously providing the

The value premium in U.S. stock returns is robust. The positive relation between average return and book-to-market equity is as strong for 1929 to 1963 as for the subsequent period studied in previous papers. A three-factor risk model explains the value premium better than the hypothesis that the book-tomarket characteristic is compensated irrespective of risk loadings. Firms with high ratios of book value to the market value of common equity have higher average returns than firms with low book-to-market ratios (Rosenberg, Reid, and Lanstein (1985)). Because the capital asset pricing model (CAPM) of Sharpe (1964) and Lintner (1965) does not explain this pattern in average returns, it is typically called an anomaly. There are four common explanations for the book-to-market (BE/ME) anomaly. One says that the positive relation between BE/ME and average return (the so-called value premium) is a chance result unlikely to be observed out of sample (Black (1993), MacKinlay (1995)). Out-of-s...

Seasoned equity issuers can raise reported earnings by altering discretionary accounting accruals. We find that issuers who adjust discretionary current accruals to report higher net income prior to the o#ering have lower post-issue long-run abnormal stock returns and net income. Interestingly, the relation between discretionary current accruals and future returns (adjusted for firm size and book-to-market ratio) is stronger and more persistent for seasoned equity issuers than for non-issuers. The evidence is consistent with investors naively extrapolating pre-issue earnings without fully adjusting for the potential manipulation of reported earnings. # 1998 Elsevier Science S.A. All rights reserved.

This paper addresses the following basic capital budgeting question: Suppose that crosssectional differences in stock returns can be predicted based on variables other than beta (e.g., book-to-market), and that this predictability reflects market irrationality rather than compensation for fundamental risk. In this setting, how should companies determine hurdle rates? I show how factors such as managerial tune horizons and financial constraints affect the optimal hurdle rate. Under some circumstances, beta can be useful as a capital budgeting tool, even if it is of no use in predicting stock returns.

We investigate the portfolio choices of mean-variance-optimizing investors who use sample evidence to update prior beliefs centered on either risk-based or characteristic-based pricing models. With dogmatic beliefs in such models and an unconstrained ratio of position size to capital, optimal portfolios can differ across models to economically significant degrees. The differences are substantially reduced by modest uncertainty about the models ’ pricing abilities. When the ratio of position size to capital is subject to realistic constraints, the differences in portfolios across models become even less important, nonexistent in some cases.

We show that corporate investment decisions can explain conditional dynamics in expected asset returns. Our approach is similar in spirit to Berk, Green, and Naik (1999), but we introduce to the investment problem operating leverage, reversible real options, fixed adjustment costs, and finite growth opportunities. Asset betas vary over time with historical investment decisions and current product market demand. Book-to-market effects emerge and relate to operating leverage, while size captures the residual importance of growth options relative to as-sets in place. We estimate and test the model using simulation methods and reproduce portfolio excess returns comparable to the data. Corporate investment decisions are often evaluated in a real options context, 1 and option exercise can change the riskiness of a firm in various ways. For example, if growth opportunities are finite, the decision to invest changes the ratio of growth options to assets in place. Additionally, the resulting increase

Statistical inference in long-horizon event studies has been hampered by the fact that abnormal returns are neither normally distributed nor independent. This study presents a new approach to inference that overcomes these difficulties and dominates other popular testing methods. I illustrate the use of the methodology by examining the long-horizon returns of initial public offerings ~IPOs!. I find that the Fama and French ~1993! three-factor model is inconsistent with the observed long-horizon price performance of these IPOs, whereas a characteristic-based model cannot be rejected. RECENT EMPIRICAL STUDIES IN FINANCE document systematic long-run abnormal price reactions subsequent to numerous corporate activities. 1 Since these results imply that stock prices react with a long delay to publicly available information, they appear to be at odds with the Efficient Markets Hypothesis ~EMH!. Long-run event studies, however, are subject to serious statistical difficulties

This paper incorporates a time-varying severity of disasters into the hypothesis proposed by Rietz (1988) and Barro (2006) that risk premia result from the possibility of rare large disasters. During a disaster an asset’s fundamental value falls by a time-varying amount. This in turn generates time-varying risk premia and thus volatile asset prices and return predictability. Using the recent technique of linearity-generating processes, the model is tractable and all prices are exactly solved in closed form. In this paper’s framework, the following empirical regularities can be understood quantitatively: (i) equity premium puzzle; (ii) risk-free rate puzzle; (iii) excess volatility puzzle; (iv) predictability of aggregate stock market returns with price-dividend ratios; (v) often greater explanatory power of characteristics than covariances for asset returns; (vi) upward sloping nominal yield curve; (vii) predictability of future bond excess returns and long term rates via the slope of the yield curve; (viii) corporate bond spread puzzle; (ix) high price of deep out-of-the-money puts; and (x) high put prices being followed by high stock returns. The calibration passes a variance bound test, as normal-times market volatility is consistent with the wide dispersion of disaster outcomes in the historical record. The model also extends to Epstein-Zin-Weil preferences and to a setting with many factors.

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We present a comparative analysis of two sets of competing theories of financial anomalies: (1) “behavioral ” theories relying on investor irrationality; and (2) rational “structural uncertainty” theories where investors have incomplete information about the economic environment. Each set of theories deviates from the rational expectations ideal, relaxing one, but not the other, of its two major assumptions. Despite their differing theoretical foundations, the two sets of theories share remarkable mathematical and predictive similarities and differ mainly in the labels they attach to similar modeling techniques and in the interpretations they give to resulting predictions. Their similarity leaves the theories virtually indistinguishable empirically, even as their normative implications differ significantly. This similarity, however, may point to deeper and overlooked connections between investor irrationality and rational structural uncertainty. We illustrate our ideas by examining competing theories of IPO underperformance.