"PEAD.txt: Post-Earnings-Announcement Drift Using Text "
18 September 2021, 17:30-18:30 CEST
In this talk, we look at using the language in "earnings calls." In an earnings call, senior management discusses the quarterly performance of the company with stock analysts. We use the text to recreate a classic "puzzle" related to the release of earnings information related to the longer horizon post-announcement stock performance. Stock prices react to good (bad) news in an earnings announcement -- not a puzzle. That stock prices continue to trend after the announcement of good (bad) news is a puzzle. We recreate this puzzle using the text from the earnings call. This gives us a richer insight into the puzzle as we can see from the text what is most correlated with the unusual behavior.
Bryan Routledge is an Associate Professor of Finance at the Tepper School of Business, Carnegie Mellon University. He received his Ph.D. from the University of British Columbia in 1996. His research includes modeling the risk premia, blockchain incentives, cryptocurrency derivatives and price stability, natural language processing, data ethics, and machine learning. He is an associate editor at the Journal of Quantitative Finance and the Critical Review of Finance, and the Secretary Treasurer of the Western Finance Association. At the Tepper School he has taught a broad set of courses including, Venture Capital, Fintech, Alpha, Finance core, and Business Science. He was the co-chair of the working group that helped lead the design and construction of the Tepper Quad project that was completed in 2018.
The talks will be held online. For more information, write to email@example.com.