A multilevel analysis of financial institutions' systemic exposure from local and system-wide information.

ABSTRACT: In the aftermath of the financial crisis of 2007-2009, the growing body of literature on financial networks has widely documented the predictive power of topological characteristics (e.g., degree centrality measures) to explain the systemic impact or systemic exposure of financial institutions. This study shows that considering alternative topological measures based on local sub-network environment improves our ability to identify systemic institutions. To provide empirical evidence, we apply a two-step procedure. First, we recover network communities (i.e., close-peer environment) on a spillover network of financial institutions. Second, we regress alternative measures of vulnerability (i.e. firm's losses)on three levels of topological measures: the global level (i.e., firm topological ch

SUBMITTER: Gandica Y 

PROVIDER: S-EPMC7573582 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature