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dc.contributor.authorPodobnik, B.-
dc.contributor.authorHorvatic, D.-
dc.contributor.authorBertella, Mário Augusto-
dc.contributor.authorFeng, L.-
dc.contributor.authorHuang, X.-
dc.contributor.authorLi, B.-
dc.identifier.citationEpl. Mulhouse: Epl Association, European Physical Society, v. 106, n. 6, 6 p., 2014.-
dc.description.abstractComplex non-linear interactions between banks and assets we model by two time-dependent Erdos-Renyi network models where each node, representing a bank, can invest either to a single asset (model I) or multiple assets (model II). We use a dynamical network approach to evaluate the collective financial failure -systemic risk- quantified by the fraction of active nodes. The systemic risk can be calculated over any future time period, divided into sub-periods, where within each sub-period banks may contiguously fail due to links to either i) assets or ii) other banks, controlled by two parameters, probability of internal failure p and threshold T-h ("solvency" parameter). The systemic risk decreases with the average network degree faster when all assets are equally distributed across banks than if assets are randomly distributed. The more inactive banks each bank can sustain (smaller T-h), the smaller the systemic risk -for some Th values in I we report a discontinuity in systemic risk. When contiguous spreading becomes stochastic ii) controlled by probability p(2) -a condition for the bank to be solvent (active) is stochasticthe- systemic risk decreases with decreasing p(2). We analyse the asset allocation for the U.S. banks. Copyright (C) EPLA, 2014en
dc.publisherEpl Association, European Physical Society-
dc.sourceWeb of Science-
dc.titleSystemic risk in dynamical networks with stochastic failure criterionen
dc.contributor.institutionUniv Rijeka-
dc.contributor.institutionZagreb Sch Econ & Management-
dc.contributor.institutionUniv Ljubljana-
dc.contributor.institutionUniv Zagreb-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionNatl Univ Singapore-
dc.contributor.institutionBoston Univ-
dc.contributor.institutionTongji Univ-
dc.description.affiliationUniv Rijeka, Fac Civil Engn, Rijeka 51000, Croatia-
dc.description.affiliationZagreb Sch Econ & Management, Zagreb 10000, Croatia-
dc.description.affiliationUniv Ljubljana, Fac Econ, Ljubljana 1000, Slovenia-
dc.description.affiliationUniv Zagreb, Fac Sci, Zagreb 10000, Croatia-
dc.description.affiliationSao Paulo State Univ UNESP Araraquara, Dept Econ, BR-14800901 Sao Paulo, Brazil-
dc.description.affiliationNatl Univ Singapore, Dept Phys, Singapore 117546, Singapore-
dc.description.affiliationNatl Univ Singapore, Ctr Computat Sci & Engn, Singapore 117546, Singapore-
dc.description.affiliationBoston Univ, Dept Phys, Boston, MA 02215 USA-
dc.description.affiliationTongji Univ, Sch Phys Sci & Engn, Ctr Phonon & Thermal Energy Sci, Shanghai 200092, Peoples R China-
dc.description.affiliationUnespSao Paulo State Univ UNESP Araraquara, Dept Econ, BR-14800901 Sao Paulo, Brazil-
dc.rights.accessRightsAcesso restrito-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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