We examine the relation between insider trading and corporate disclosure of cyberattacks. We distinguish between companies that voluntarily disclosed cyberattacks and those that withheld information on the incidents, and parties outside the attacked company later discovered the incident. We find...

Using daily stock returns, we estimate the precision of information during earnings and non-earnings announcement days, and find that although the precision of information in daily stock returns increases during earnings announcement days, it explains less of the variation in expected returns...

The paper demonstrates empirically that GAAP earnings have properties to serve as a substitute for dividends in equity valuation analysis. Dividends reduce subsequent GAAP earnings, and quot;intrinsicquot; equity prices calculated by forecasting earnings are thus reduced by current dividends....

Estimates and projections are embedded in most financial statement items. These estimates potentially improve the relevance of financial information by providing managers the means to convey to investors forward-looking, inside information (e.g., on future collections from customers via the bad...

The immediate expensing of Ramp;D expenditures is often justified by the conservatism principle. However, no accounting procedure consistently applied can be conservative throughout the firm' life. We ask the following questions: (a) When is the expensing of Ramp;D conservative and when is it...

We combine a fundamental property of accruals and a behavioral phenomenon to provide an explanation for the accrual anomaly. The fundamental property is: accruals that originate must subsequently reverse. The behavioral phenomenon is: individuals tend to underestimate the variance of noisy...

The fixed-effects specification is often used in panel datasets as a way of dealing with correlated omitted variables. A review of recent accounting publications reveals that while researchers are generally aware of the need to include fixed-effects in empirical models when using panel datasets...

Out-of-sample prediction of profitability is a critical step in fundamental analysis and yet even sophisticated regression models do not generate predictions that significantly outperform random walk predictions. We employ random forests with classification trees, a method from machine learning,...

We suggest that the failure of investors to distinguish between an earnings component's autocorrelation coefficient (unconditional persistence) and the marginal contribution of that component's persistence to the persistence of earnings (conditional persistence) provides a partial explanation to...

We investigate whether and how the complexity of derivatives influences analysts' earnings forecast properties. Using a difference-in-differences design, we find that, relative to a matched control sample of non-users, analysts' earnings forecasts for new derivatives users are less accurate and...