This paper assesses different approaches to testing the cross-sectional valuation effects of an event for firms with different characteristics. Standard cross-sectional return regressions typically reject at the 1% significance level more than 25% of the time in non-event periods, suggesting...

We present a statistical model that accounts for persistent fluctuations in characteristic-sorted portfolio returns. The model provides a simple formula for adjusting the standard errors of expected return estimates. With plausible parameter values, the adjusted standard errors double, casting...

We examine the information content of option and equity volumes when trade direction is unobserved. In a multimarket symmetric information model, we show that equity short-sale costs result in a negative relation between relative option volume and future firm value. In our empirical tests,...

Using newly-mandated disclosures, we show some fund managers retain a fraction of securities lending income by employing in-house lending agents. In a model with heterogeneous investors, we find this retention leads funds to "reach for lending fees" by overweighting high-fee stocks that...

Kandel and Stambaugh (1996) demonstrate that forecasting variables with weak statistical support in predictive return regressions can exert considerable economic influence on portfolio decisions. Using a Bayesian vector autoregression framework with stochastic volatility in market returns and...

We establish a link between firms managing investors' performance expectations, earnings announcement premia, and cyclical patterns (i.e., seasonalities) in returns. Firms that are more likely to manage expectations toward beatable levels predictably earn lower returns before, and higher returns...

We measure the impact of reputation for proxy fighting on investor activism by estimating a dynamic model in which activists engage a sequence of target firms. Our estimation produces an evolving reputation measure for each activist and quantifies its impact on campaign frequency and outcomes....

I assess time-series return predictability using a weighted least squares estimator that is around 25% more efficient than ordinary least squares (OLS) because it incorporates time-varying volatility into its point estimates. Traditional predictors, such as the dividend yield, perform better in-...