English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In the aftermath of the financial crisis, the growing literature on financialnetworks has widely documented the predictive power of topologicalcharacteristics (e.g. degree centrality measures) to explain the systemicimpact or systemic vulnerability of financial institutions. In this work, weshow that considering alternative topological measures based on localsub-network environment improves our ability to identify systemic institutions.To provide empirical evidence, we apply a two-step procedure. First, we recovernetwork communities (i.e. close-peer environment) on a spillover network offinancial institutions. Second, we regress alternative measures ofvulnerability on three levels of topological measures: the global level (i.e.firm topological characteristics computed over the whole system), local level(i.e. firm topological characteristics computed over the community) andaggregated level by averaging individual characteristics over the community.The sample includes $46$ financial institutions (banks, broker-dealers,insurance and real-estate companies) listed in the Standard \& Poor's 500index. Our results confirm the informational content of topological metricsbased on close-peer environment. Such information is different from the oneembeds in traditional system wide topological metrics and is proved to bepredictor of distress for financial institutions in time of crisis.

A multilevel analysis to systemic exposure: insights from local and system-wide information