Sentometrics: An Overview of Methodology and Applications
Speaker: David Ardia, Professeur agrégé, GERAD & HEC Montréal
Abstract
The advent of massive amounts of textual data has spurred the development of econometric methodology to transform qualitative sentiment data into quantitative sentiment variables, and to use those variables in an econometric analysis of the relationships between sentiment and other variables. This seminar will present this new research field and illustrate possible applications in economics and finance.
Social Media as a Bank Run Catalyst
Speaker: Juan Imbet, Assistant Professor of Finance at the Université Paris Dauphine – PSL
Coauthors: Tony Cookson, Corbin Fox, Javier Gil-Bazo and Christoph Schiller
Abstract
Social media fueled a bank run on Silicon Valley Bank (SVB), and the effects were felt broadly in the U.S. banking industry. We employ comprehensive Twitter data to show that preexisting exposure to social media predicts bank stock market losses in the run period even after controlling for bank characteristics related to run risk (i.e., mark-to-market losses and uninsured deposits). Moreover, we show that social media amplifies these bank run risk factors. During the run period, we find the intensity of Twitter conversation about a bank predicts stock market losses at the hourly frequency. This effect is stronger for banks with bank run risk factors. At even higher frequency, tweets in the run period with negative sentiment translate into immediate stock market losses. These high frequency effects are stronger when tweets are authored by members of the Twitter startup community (who are likely depositors) and contain keywords related to contagion. These results are consistent with depositors using Twitter to communicate in real time during the bank run.