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...

Previous research finds that historical seasonal earnings rank negatively predicts stock returns surrounding earnings announcements (EAs) in China’s A-share markets. We examine whether management earnings forecasts (MEFs) help reduce the stock return seasonality associated with earnings...

We constructed forecasts of earnings forecasts using data on 406 firms and forecasts made by 5419 individuals with on average 25 forecasts per individual. We verified previously found predictors, which are the average of the most recent available forecast for each forecaster and the difference...

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...

An analysis of about 300000 earnings forecasts, created by 18000 individual forecasters for earnings of over 300 S&P listed firms, shows that these forecasts are predictable to a large extent using a statistical model that includes publicly available information. When we focus on the...

More than 650 U.S. public company executives predict the stock price response to their quarterly financial reports and share their prediction after under a nondisclosure agreement. Despite having full knowledge of the reports before their release, executives’ estimates differ from realized...

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...

This paper uses a dataset of more than 900,000 news stories to test whether news predicts stock returns. We measure sentiment with the Harvard psychosocial dictionary used by Tetlock, Saar-Tsechansky, and Macskassy (2008), the financial dictionary of Loughran and McDonald (2011), and a...

Releases of key macroeconomic indicators are closely watched by financial markets. We investigate the role of expectation dispersion and economic uncertainty for the stock-market reaction to indicator releases. We find that the strength of the financial market response to news decreases with the...

Releases of key macroeconomic indicators are closely watched by financial markets. We investigate the role of expectation dispersion and economic uncertainty for the stock-market reaction to indicator releases. We find that the strength of the financial market response to news decreases with the...