News and Networks: Using Text Analytics to Assess Bank Networks During COVID-19 Crisis
52 Pages Posted: 30 Mar 2021 Last revised: 9 Sep 2021
Date Written: March 29, 2021
We study the 'interconnectedness' of stress-tested banks by exploiting how they are mentioned together in the context of financial news. We start by constructing weekly co-occurrence network matrices following Ronnqvist and Sarlin (2015) text-to-network approach. Using the COVID-19 pandemic as an external shock, we examine how bank networks behave during high stress periods. We find that banks become more interconnected during peaks of COVID-19 induced stress. We put forth a new measure of systemic risk that utilizes text-based eigenvector centrality. This measure provides a more stable ranking system than the traditional SRISK measure during both high and low stress periods.
Keywords: Bank Networks, Text Analysis, Systemic Risk, COVID-19, Financial Stability
JEL Classification: G1, D85, L14, G20, G32, G38
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