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Systemic risk in dynamical networks with stochastic failure criterion
  • Univ Rijeka
  • Zagreb Sch Econ & Management
  • Univ Ljubljana
  • Univ Zagreb
  • Universidade Estadual Paulista (UNESP)
  • Natl Univ Singapore
  • Boston Univ
  • Tongji Univ
Complex 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, 2014
Issue Date: 
Epl. Mulhouse: Epl Association, European Physical Society, v. 106, n. 6, 6 p., 2014.
Time Duration: 
Epl Association, European Physical Society
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Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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