This paper proposes a new approach to control the effects of time-varying parameters on the estimates of abnormal returns. Event studies usually assume that the parameters of the market model are stable. Using a sample of firm takeovers, however, I find that this assumption is indeed rejected....

The calculation of expected returns is a necessary ingredient in data processing for an event study. The method most commonly used, the market model, often fails to meet the OLS requirement of normally distributed residuals, and tends to furnish regression output (low R2, and insignificant t-...

The results of academic and practitioners' event studies are often translated from excess log returns into excess dollar returns. The prior literature argues for a difference between the statistical significance of excess log returns and that of excess dollar returns. In contrast, we show...

This paper studies the long-run risk embedded in the news about future investment-specific technology (IST). The IST news shock, which reflects future technological improvements in the production of investment goods such as computers, machines, and equipment, causes persistent future consumption...

We estimate agents' expectations about future fundamentals using a dynamic stochastic generalequilibrium model augmented with anticipated shocks. Accounting for agents' expectations atthe business cycle horizon results in aggregate risk factor innovations that have significant explanatory power...

We find that the FOMC-announcement-day return premium earned by a firm is positively related to the increase in its ex ante, option-implied skewness prior to the announcement. This finding is consistent with: (1) the existence of an announcement-day Fed put that is partially anticipated by the...

We analyze the joint out-of-sample predictive ability of a comprehensive set of 299 firm characteristics for cross-sectional stock returns. We develop a cross-sectional out-of-sample R2 statistic that provides an informative measure of the accuracy of cross-sectional return forecasts in terms of...

We propose a new asset-pricing framework in which all securities' signals are used to predict each individual return. While the literature focuses on each security's own- signal predictability, assuming an equal strength across securities, our framework is flexible and includes...