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Completeness, interconnectedness and distribution of interbank exposures-a parameterized analysis of the stability of financial networks

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  • Angelika Sachs

Abstract

This paper assesses the impact of a certain structure of interbank exposures on the stability of a stylized financial system. Given a certain balance sheet structure of financial institutions, a large number of valid matrices of interbank exposures is created by a random generator. Assuming a certain loss given default, domino effects are simulated. The main results are, first, that financial stability depends not only on the completeness and interconnectedness of the network, but also on the distribution of interbank exposures within the system (measured by entropy). Second, looking at random graphs, the sign of the correlation between the degree of equality of the distribution of claims and financial stability depends on the connectivity of the financial system as well as on additional parameters that affect the vulnerability of the system to interbank contagion. Third, the more concentrated the assets are within a money center model, the less stable it is. Fourth, a money center model with asset concentration among core banks is less stable than a random graph with banks of homogeneous size.

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  • Angelika Sachs, 2014. "Completeness, interconnectedness and distribution of interbank exposures-a parameterized analysis of the stability of financial networks," Quantitative Finance, Taylor & Francis Journals, vol. 14(9), pages 1677-1692, September.
    • Handle: RePEc:taf:quantf:v:14:y:2014:i:9:p:1677-1692
    DOI: 10.1080/14697688.2012.749421
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    References listed on IDEAS

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    1. Christian Upper, 2007. "Using counterfactual simulations to assess the danger of contagion in interbank markets," BIS Working Papers 234, Bank for International Settlements.
    2. Simon Wells, 2004. "Financial interlinkages in the United Kingdom's interbank market and the risk of contagion," Bank of England working papers 230, Bank of England.
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    4. Marco A. Espinosa‐Vega & Juan Solé, 2011. "Cross‐border financial surveillance: a network perspective," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 3(3), pages 182-205, August.
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    6. Paul Glasserman & H. Peyton Young, 2015. "Contagion in Financial Markets," Working Papers 15-21, Office of Financial Research, US Department of the Treasury.
    7. 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.
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    9. Domenico Di Gangi & Fabrizio Lillo & Davide Pirino, 2015. "Assessing systemic risk due to fire sales spillover through maximum entropy network reconstruction," Papers 1509.00607, arXiv.org, revised Jul 2018.
    10. Yongli Li & Guanghe Liu & Paolo Pin, 2018. "Network-based risk measurements for interbank systems," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-18, July.
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    12. 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.
    13. Ozili, Peterson K, 2017. "Earnings Management in Interconnected Networks: A Perspective," MPRA Paper 92647, University Library of Munich, Germany.
    14. Paul Glasserman & H. Peyton Young, 2016. "Contagion in Financial Networks," Journal of Economic Literature, American Economic Association, vol. 54(3), pages 779-831, September.
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    16. Di Gangi, Domenico & Lillo, Fabrizio & Pirino, Davide, 2018. "Assessing systemic risk due to fire sales spillover through maximum entropy network reconstruction," Journal of Economic Dynamics and Control, Elsevier, vol. 94(C), pages 117-141.
    17. Arnd Hübsch & Ursula Walther, 2017. "The impact of network inhomogeneities on contagion and system stability," Annals of Operations Research, Springer, vol. 254(1), pages 61-87, July.
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