We apply state-of-the-art financial machine learning to assess the return-predictive value of more than 45,000 earnings announcements on a majority of S&P1500 constituents. To represent the diverse information content of earnings announcements, we generate predictor variables based on various...

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...