University of Limerick Institutional Repository

A framework for analyzing contagion in assortative banking networks

DSpace Repository

Show simple item record

dc.contributor.author Hurd, Thomas R
dc.contributor.author Gleeson, James P.
dc.contributor.author Melnik, Sergey
dc.date.accessioned 2017-05-11T10:28:05Z
dc.date.available 2017-05-11T10:28:05Z
dc.date.issued 2017
dc.identifier.uri http://hdl.handle.net/10344/5791
dc.description peer-reviewed en_US
dc.description.abstract We introduce a probabilistic framework that represents stylized banking networks with the aim of predicting the size of contagion events. Most previous work on random financial networks assumes independent connections between banks, whereas our framework explicitly allows for (dis) assortative edge probabilities (i.e., a tendency for small banks to link to large banks). We analyze default cascades triggered by shocking the network and find that the cascade can be understood as an explicit iterated mapping on a set of edge probabilities that converges to a fixed point. We derive a cascade condition, analogous to the basic reproduction number R-0 in epidemic modelling, that characterizes whether or not a single initially defaulted bank can trigger a cascade that extends to a finite fraction of the infinite network. This cascade condition is an easily computed measure of the systemic risk inherent in a given banking network topology. We use percolation theory for random networks to derive a formula for the frequency of global cascades. These analytical results are shown to provide limited quantitative agreement with Monte Carlo simulation studies of finite-sized networks. We show that edge-assortativity, the propensity of nodes to connect to similar nodes, can have a strong effect on the level of systemic risk as measured by the cascade condition. However, the effect of assortativity on systemic risk is subtle, and we propose a simple graph theoretic quantity, which we call the graph-assortativity coefficient, that can be used to assess systemic risk. en_US
dc.language.iso eng en_US
dc.publisher Public Library of Science en_US
dc.relation.ispartofseries PLoS ONe;12 (2), e0170579
dc.relation.uri http://dx.doi.org/10.1371/journal.pone.0170579
dc.subject topology en_US
dc.subject market en_US
dc.subject model en_US
dc.title A framework for analyzing contagion in assortative banking networks en_US
dc.type info:eu-repo/semantics/article en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.date.updated 2017-05-11T10:21:46Z
dc.description.version PUBLISHED
dc.identifier.doi 10.1371/journal.pone.0170579
dc.contributor.sponsor Natural Sciences and Engineering Research Council of Canada en_US
dc.contributor.sponsor Global Risk Institute for Financial Services of Canada en_US
dc.contributor.sponsor SFI en_US
dc.contributor.sponsor IRC en_US
dc.relation.projectid 11/PI/1026 en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US
dc.internal.rssid 2702216
dc.internal.copyrightchecked Yes
dc.identifier.journaltitle Plos One
dc.description.status peer-reviewed


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search ULIR


Browse

My Account

Statistics