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...

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...