An earnings prediction approach to examining intercompany information transfers

Abstract We assess potential information transfers by examining the association between the earnings announcements of early and late announcers in an industry. Our earnings prediction models are statistically significant much more frequently than would be expected by chance. The models suggest potential positive information transfers on average, but there is substantial cross-industry variation in the strength of this relation. We find that the greatest price reactions by nonannouncers to same-industry earnings announcements occur in industries with the greatest earnings comovement