If asset returns have systematic skewness, expected returns should include rewards for accepting this risk. We formalize this intuition with an asset pricing model that incorporates conditional skewness. Our results show that conditional skewness helps explain the cross-sectional variation of expected returns across assets and is significant even when factors based on size and book-to-market are included. Systematic skewness is economically important and commands a risk premium, on average, of 3.60 percent per year. Our results suggest that the momentum effect is related to systematic skewness. The low expected return momentum portfolios have higher skewness than high expected return portfolios. THE SINGLE FACTOR CAPITAL ASSET PRICING MODEL ~CAPM! of Sharpe ~1964! and Lintner ~1965! has come under recent scrutiny. Tests indicate that the crossasset variation in expected returns cannot be explained by the market beta alone. For example, a growing number of studies show that “fundamental” variables such as size, book-to-market value, and price to earnings ratios

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 efficient market hypothesis has been widely tested and, with few exceptions, found consistent with the data in a wide variety of markets: the New York and American Stock Exchanges, the Australian, English, and German stock markets, various commodity futures markets, the Over-the-Counter markets, the corporate and government bond markets, the option market, and the market for seats on the New York Stock Exchange. Yet, in a manner remarkably similar to that described by Thomas Kuhn in his book, The Structure of Scientific Revolutions, we seem to be entering a stage where widely scattered and as yet incohesive evidence is arising which seems to be inconsistent with the theory. As better data become available (e.g., daily stock price data) and as our econometric sophistication increases, we are beginning to find inconsistencies that our cruder data and techniques missed in the past. It is evidence which we will not be able to ignore. The purpose of this special issue of the Journal of Financial Economics is to bring together a number of these scattered pieces of anomalous evidence regarding Market Efficiency. As Ball (1978) points out in his survey article: taken individually many scattered pieces of evidence on the reaction of stock prices to earnings announcements which are inconsistent with the theory don’t amount to much. Yet viewed as a whole, these pieces of evidence begin to stack up in a manner which make a much stronger case for the necessity to carefully review both our acceptance of the efficient market theory and our methodological procedures.

Abstract not found

This paper investigates nonlinear pricing kernels in which the risk factor is endogenously determined and preferences restrict the definition of the pricing kernel. These kernels potentially generate the empirical performance of nonlinear and multifactor models, while maintaining empirical power and avoiding ad hoc specifications of factors or functional form. Our test results indicate that preferencerestricted nonlinear pricing kernels are both admissible for the cross section of returns and are able to significantly improve upon linear single- and multifactor kernels. Further, the nonlinearities in the pricing kernel drive out the importance of the factors in the linear multi-factor model. A PRINCIPAL IMPLICATION OF THE Capital Asset Pricing Model ~CAPM! is that the pricing kernel is linear in a single factor, the portfolio of aggregate wealth. Numerous studies over the past two decades have documented violations of this restriction. 1 In response, researchers have examined the performance of alternative models of asset prices. These models have generally fallen into two classes: ~1! multifactor models such as Ross ’ APT or Merton’s ICAPM, in which factors in addition to the market return determine asset prices; or ~2! nonparametric models, such as Bansal et al. ~1993!, Bansal and Viswanathan ~1993!, and Chapman ~1997!, in which the pricing kernel is not

I review empirical research on the relation between capital markets and financial statements.The principal sources of demand for capital markets research in accounting are fundamental analysis and valuation, tests of market efficiency, and the role of accounting numbers in contracts and the political process.The capital markets research topics of current interest to researchers include tests of market efficiency with respect to accounting information, fundamental analysis, and value relevance of financial reporting.Evidence from research on these topics is likely to be helpful in capital market investment decisions, accounting standard setting, and corporate financial

In this paper we investigate the properties of the standard two-pass methodology of testing beta pricing models with misspecified factors. In a setting where a factor is useless, defined as being independent of all the asse t returns, we provide theoretical results and simulation evidence that the second-pass cross-sectional regression tends to find the beta risk of the useless factor priced more often than it should. More surprisingly, this misspecification bias exacerbates when the number of time series observations increases. Possible ways of detecting useless factors are also examined. When testing asset pricing models relating risk premiums on assets to their betas, the primary question of interest is whether the beta risk of a particular factor is priced (i.e., whether the estimated risk premium associated with a given factor is significantly di#erent from zero). Black, Jensen, and Scholes (1972) and Fama and MacBeth (1973) develop a two-pass methodology in which the beta of each asset with respect to a factor is estimated in a first-pass time series regression, and estimated betas are then used in second-pass cross-sectional regressions (CSRs) to estimate the risk premium of the factor. This two-pass methodology is very intuitive and has been widely used in the literature. The properties of the test statistics and goodness-of-fit measures under the two-pass methodology are usually developed under the assumptions that the asset pricing model is correctly specified and that the factors are correctly identified. Shanken (1992) provides an excellent discussion of this two-pass methodology, especially the large sample properties of the two-pass CSR for the correctly specified model under the assumption that returns are conditionally homoskedastic. Jagannathan and Wa...

We report on six large-scale financial markets experiments that were designed to test two of the most basic propositions of modern asset pricing theory, namely, that the interaction between risk averse agents in a competitive market leads to equilibration, and that, in equilibrium, risk premia are solely determined by covariance with aggregate risk. We designed the experiments within the framework suggested by two theoretical models, namely, Arrow and Debreu’s complete-markets model, and the Sharpe-Lintner-Mossin Capital Asset Pricing Model (CAPM). This framework enabled us to measure how far our markets were from equilibrium at any point in time, thereby allowing us to gauge the success of the models. The distance measures do not require knowledge of the (uncontrollable) level and dispersion of risk aversion among subjects, and adjust for the impact of progressive trading on the eventual equilibrium. Unlike in our earlier, thin-markets experiments, we discovered swift convergence towards equilibrium prices of Arrow and Debreu’s model or the CAPM. This discovery is significant, because subjects always lacked the information to deliberately set asset prices using either model. Sometimes, however, the equilibrium was not found to be robust, with markets readily veering away, apparently as a result of deviations of subjective beliefs from objective probabilities. Still, we find evidence that this did not destroy the tendency for markets to equilibrate as predicted by the theory. In each experiment, we formally test and reject the hypothesis that prices are a random walk, in favor of stochastic convergence towards CAPM and Arrow Debreu equilibrium.

financial support from the Pigott-PACCAR professorship at the University of Washington. Previous drafts of the this paper were entitled, " Conditional Performance Evaluation." Performance Evaluation with Stochastic Discount Factors This paper uses a general asset pricing framework for evaluating the performance of mutual funds. Abnormal returns are formed by multiplying a fund's gross return by a stochastic discount factor and subtracting one. We compare the performance of a large

Modern finance has generated a set of formal models of the workings of financial markets that certainly excel in terms of mathematical elegance. But abstract beauty and logical appeal do not guarantee scientific validity. The illustrious late Richard Feynman, professor of physics at Caltech, made the same observation when he discussed the derivation of the law of gravitational potential energy from the "axiom" of conservation of energy. (See the above quote.) Fortunately for physicists, there is ample evidence that the law of gravitational potential energy is correct (to a certain degree). In contrast, there appears to be surprisingly little scientific support for even the most widely used financial model, namely, the CAPM. One can sympathize with E. Fama and K. French when they have recently begun to promote a pricing model that is based entirely on statistical regularities, even if it begs the question why it is more successful. To put this di#erently, asset pricing is paradoxical