We develop a measure of how information events impact investors' perceptions of risk that is broadly applicable and simple to implement. We derive this measure from an option-pricing model where investors anticipate an announcement that simultaneously conveys information on the announcer's...

We investigate whether mandatory earnings announcement date forecasts are informative to investors and the informational tradeoffs between mandatory and voluntary forecasts. We find: (i) The percentages of the quarter's earnings news conveyed by mandatory China and voluntary US forecasts are...

This paper examines the relation between firm-level implied volatility skew and the likelihood of extreme negative events, or crash risk. I show that volatility skew identifies which firms are likely to experience crashes, but only in short-window earnings announcement periods. The predictive...

We address whether analysts bias earnings forecast revisions and convey the bias using forecast revision consistency, i.e., the extent to which analyst reports with earnings forecast revisions include stock recommendation and target price revisions consistent in sign with the earnings forecast...

This study finds that pro-forma earnings forecasts by bidding firms during acquisitions are associated with a higher likelihood of deal completion, expedited deal closing, and with a lower acquisition premium − but only in stock-financed acquisitions. Analysts also respond to these forecasts...

We provide evidence that equity investors with limited attention are slow to incorporate how current oil price changes affect future earnings announcements. A cross-sectional equity trading strategy that exploits this inefficiency yields an annualized Sharpe Ratio of 0.57. Stock prices respond...

Firms often issue disaggregated earnings forecasts, and prior research reveals benefits to doing so. However, we hypothesize and experimentally find that the benefits of disaggregated forecasts do not necessarily carry over to the time of actual earnings announcements. Rather, disaggregated...

This study examines whether crowdsourced forecasts of earnings and revenues help investors unravel bias in earnings announcement news, which is commonly derived from analyst forecasts. Our results suggest that investors, on average, understand and price the predictive signals reflected in...

Large earnings surprises and negative earnings surprises represent more egregious errors in analysts' earnings forecasts. We find evidence consistent with our expectation that egregious forecast errors motivate analysts to work harder to develop or acquire relatively more private information in...