Systemic risk in banking networks without monte carlo simulation
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.
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.
[PDF][PDF] Systemic risk in banking networks without Monte Carlo simulation
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.
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.
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