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 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...

The purpose of this paper is to analyse the predictability of earnings information before the quarterly disclosure date. Two categories of firms are contrasted: the firms that announce better quarterly earnings than the prior period and the firms that do not. The paper uses a sample of 67...

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...

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...

I hypothesize that the stock market overreacts to management earnings forecasts because of the uncertainty surrounding them. I find that negative management forecast surprises lead to a –5.9% abnormal return around the forecast and a 1.9% correction in the 2-month period after earnings are...

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...

Using a large dataset of news releases, we study instances of investors' mistaken reaction, or misreaction, to news. We define misreaction as stock prices moving in the direction opposite to the news when it is released. We find that news tone predicts returns in the cross-section only upon the...

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...

This paper uses a dataset of more than 900,000 news stories to test whether news can predict stock returns. We measure sentiment with a proprietary Thomson-Reuters neural network. We find that daily news predicts stock returns for only 1 to 2 days, confirming previous research. Weekly news,...