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Systemic losses due to counterparty risk in a stylized banking system

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  • Birch, Annika
  • Aste, Tomaso

Abstract

We report a study of a stylized banking cascade model investigating systemic risk caused by counterparty failure using liabilities and assets to define banks' balance sheet. In our stylized system, banks can be in two states: normally operating or distressed and the state of a bank changes from normally operating to distressed whenever its liabilities are larger than the banks' assets. The banks are connected through an interbank lending network and, whenever a bank is distressed, its creditor cannot expect the loan from the distressed bank to be repaid, potentially becoming distressed themselves. We solve the problem analytically for a homogeneous system and test the robustness and generality of the results with simulations of more complex systems. We investigate the parameter space and the corresponding distribution of operating banks mapping the conditions under which the whole system is stable or unstable. This allows us to determine how financial stability of a banking system is influenced by regulatory decisions, such as leverage; we discuss the effect of central bank actions, such as quantitative easing and we determine the cost of rescuing a distressed banking system using re-capitalisation. Finally, we estimate the stability of the UK and US banking systems comparing the years 2007 and 2012 by using real data.

Suggested Citation

  • Birch, Annika & Aste, Tomaso, 2014. "Systemic losses due to counterparty risk in a stylized banking system," LSE Research Online Documents on Economics 57700, London School of Economics and Political Science, LSE Library.
  • Handle: RePEc:ehl:lserod:57700
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    Citations

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    Cited by:

    1. Daniel Grigat & Fabio Caccioli, 2017. "Reverse stress testing interbank networks," Papers 1702.08744, arXiv.org, revised Mar 2017.
    2. Tomaso Aste, 2020. "Stress testing and systemic risk measures using multivariate conditional probability," Papers 2004.06420, arXiv.org, revised May 2021.
    3. Pawe{l} Smaga & Mateusz Wili'nski & Piotr Ochnicki & Piotr Arendarski & Tomasz Gubiec, 2016. "Can banks default overnight? Modeling endogenous contagion on O/N interbank market," Papers 1603.05142, arXiv.org.
    4. Tomaso Aste, 2021. "Stress Testing and Systemic Risk Measures Using Elliptical Conditional Multivariate Probabilities," JRFM, MDPI, vol. 14(5), pages 1-17, May.
    5. Sachapon Tungsong & Fabio Caccioli & Tomaso Aste, 2017. "Relation between regional uncertainty spillovers in the global banking system," Papers 1702.05944, arXiv.org.
    6. Morteza Alaeddini & Philippe Madiès & Paul J. Reaidy & Julie Dugdale, 2023. "Interbank money market concerns and actors’ strategies—A systematic review of 21st century literature," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 573-654, April.
    7. Silva, Walmir & Kimura, Herbert & Sobreiro, Vinicius Amorim, 2017. "An analysis of the literature on systemic financial risk: A survey," Journal of Financial Stability, Elsevier, vol. 28(C), pages 91-114.

    More about this item

    Keywords

    banking crisis; counterparty risk; random field ising model; systemic risk;
    All these keywords.

    JEL classification:

    • N0 - Economic History - - General

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