Download or read book Rethinking Determinants of Trading Volume at Earnings Announcements written by Alina Lerman and published by . This book was released on 2019 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theory offers three main determinants of informationally driven trading volume at earnings announcements: pre-announcement difference in private information precision, belief divergence or differential interpretation, and signal strength. In this paper, we empirically test which theoretical determinants best explain earnings announcement volume conditional on the level of earnings news. We first document that, consistent with signal strength, there is a strong positive (negative) association between volume and both contemporaneous and immediately preceding returns for good (bad) earnings news. Next, we explicitly test the association between volume and various proxies for its three theorized determinants conditional on earnings news. We find that trading volume is highly associated with upward (downward) contemporaneous analyst revisions in the presence of good (bad) earnings news. It is also associated with future earnings surprises, the F-score, and the change in shares shorted, especially for good news firms. Volume is moderately associated with proxies of belief divergence, particularly for bad and neutral news firms. Finally, proxies for pre-announcement difference in private information precision do not appear to significantly explain trading volume for any level of earnings news. Examining financial press data we document an association between abnormal volume and coverage of a multitude of news items. Taken together, our results suggest that trading volume at earnings announcements is more reflective of the quantity and quality of information released, but its dynamics significantly vary with the nature of the disclosed news.