Single factor asset pricing models face two major hurdles: the problematic time-series properties of the ex ante market risk premium and the inability of the risk measure to account for a substantial degree of the cross-sectional variation of expected excess returns. We provide an explanation for the first failure using the following intuition: if investors know that the asset returns have conditional skewness given the information known today, the expected excess returns should include rewards for accepting skewness. We formalize this intuition with an asset pricing model which incorporates conditional skewness. We decompose the expected excess returns into components due to conditional variance and skewness. Our results show that conditional skewness is important and, when combined with the economy-wide reward for skewness, helps explain the time-variation of the ex ante market risk premiums. Conditional skewness has greater success in explaining the ex ante risk premium for the world portfolio than for the U.S. portfolio.

Several recent articles report evidence of predictability in the skewness of equity returns, raising hopes that predictability in third moments will be useful for forecasting the probability of tail events. The evidence is unfortunately difficult to interpret, partly because they were obtained mainly from parametric models of time-varying conditional skewness, and because little is known about the behavior of such models, for instance, when there are outliers. We investigate a non-parametric approach to testing for predictability in skewness. Specifically, we explore the size and power of a Runs tests, and compare this approach with other tests. A re-examination of daily market returns reveals mild evidence of predictability in skewness. Incorporating this conditional heteroskewness into standard volatility models hardly improves out-of-sample forecasts of tail probabilities.

Annotation. Advances in Quantitative Analysis of Finance and Accounting is an annual publication designed to disseminate developments in the quantitative analysis of finance and accounting. The publication is a forum for statistical and quantitative analyses of issues in finance and accounting as well as applications of quantitative methods to problems in financial management, financial accounting, and business management. The objective is to promote interaction between academic research in finance and accounting and applied research in the financial community and the accounting profession.The papers in this volume cover a wide range of topics including default risk premiums, multi-period contracts, stock market, impact of earnings change on stock price, bank regulation, dividend effect of closed-end mutual funds, income smoothing, and inflation accounting.

A presentation of classical asset pricing theory, this textbook is the only one to address the economic foundations of financial markets theory from a mathematically rigorous standpoint and to offer a self-contained critical discussion based on empirical results. Tools for understanding the economic analysis are provided, and mathematical models are presented in discrete time/finite state space for simplicity. Examples and exercises included.