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Advances in Network Analysis and its Applications

Volume 18 of the series Mathematics in Industry pp 27-56

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Systemic Risk in Banking Networks Without Monte Carlo Simulation

  • James P. GleesonAffiliated withMACSI, Department of Mathematics and Statistics, University of Limerick Email author 
  • , T. R. HurdAffiliated withDepartment of Mathematics and Statistics, McMaster University
  • , Sergey MelnikAffiliated withMACSI, Department of Mathematics and Statistics, University of Limerick
  • , Adam HackettAffiliated withMACSI, Department of Mathematics and Statistics, University of Limerick

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Abstract

An analytical approach to calculating the expected size of contagion events in models of banking networks is presented. The method is applicable to networks with arbitrary degree distributions, permits cascades to be initiated by the default of one or more banks, and includes liquidity risk effects. Theoretical results are validated by comparison with Monte Carlo simulations, and may be used to assess the stability of a given banking network topology.