We study the behavior of short sellers as informed market participants and examine potential sources of their information. Using a newly available dataset with high-frequency short sales data, we find evidence of significant increases in short sales immediately prior to large insider sales, but...

Using a machine learning approach to analyze 12.8 million tweets posted by S&P 1500 firms from 2012 to 2016, we find that firms time financial tweets around earnings announcements, accounting filings as well as other important corporate events, and are more likely to use media (images or video)...

We identify a specific organizational resource in brokerage houses—information sharing among analyst colleagues who cover economically related industries along a supply chain. We hypothesize that this resource constitutes a knowledge asset that benefits analyst research and allows analysts to...

We study the behavior of short sellers as informed market participants and examine potential sources of their information. Using a newly available dataset with high-frequency short sales data, we find evidence of significant increases in short sales immediately prior to large insider sales, but...

This paper tests several predictions from an information diffusion framework in the quarterly earnings announcement setting. First, post-announcement drift is documented only for earnings announcements that have high information content (uncertainty), measured by high abnormal trading volume and...