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.
This event is Supported by the Luxembourg National Research Fund (2022/17573036)
