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Systemic losses in banking networks: indirect interaction of nodes via asset prices

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  • Igor Tsatskis

    (Financial Services Authority, London)

Abstract

A simple banking network model is proposed which features multiple waves of bank defaults and is analytically solvable in the limiting case of an infinitely large homogeneous network. The model is a collection of nodes representing individual banks; associated with each node is a balance sheet consisting of assets and liabilities. Initial node failures are triggered by external correlated shocks applied to the asset sides of the balance sheets. These defaults lead to further reductions in asset values of all nodes which in turn produce additional failures, and so on. This mechanism induces indirect interactions between the nodes and leads to a cascade of defaults. There are no interbank links, and therefore no direct interactions, between the nodes. The resulting probability distribution for the total (direct plus systemic) network loss can be viewed as a modification of the well-known Vasicek distribution.

Suggested Citation

  • Igor Tsatskis, 2012. "Systemic losses in banking networks: indirect interaction of nodes via asset prices," Papers 1203.6778, arXiv.org.
  • Handle: RePEc:arx:papers:1203.6778
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    File URL: http://arxiv.org/pdf/1203.6778
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    References listed on IDEAS

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    1. Gai, Prasanna & Kapadia, Sujit, 2010. "Contagion in financial networks," Bank of England working papers 383, Bank of England.
    2. Nier, Erlend & Yang, Jing & Yorulmazer, Tanju & Alentorn, Amadeo, 2007. "Network models and financial stability," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 2033-2060, June.
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    Cited by:

    1. Marc van Kralingen & Diego Garlaschelli & Karolina Scholtus & Iman van Lelyveld, 2020. "Crowded trades, market clustering, and price instability," Tinbergen Institute Discussion Papers 20-007/II, Tinbergen Institute.
    2. Annika Birch & Tomaso Aste, 2014. "Systemic Losses Due to Counter Party Risk in a Stylized Banking System," Papers 1402.3688, arXiv.org.
    3. Richard Bookstaber & Mark Paddrik & Brian Tivnan, 2018. "An agent-based model for financial vulnerability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(2), pages 433-466, July.
    4. Dror Y. Kenett & Sary Levy-Carciente & Adam Avakian & H. Eugene Stanley & Shlomo Havlin, 2015. "Dynamical Macroprudential Stress Testing Using Network Theory," Working Papers 15-12, Office of Financial Research, US Department of the Treasury.

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