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Systemic risk in banking networks: Advantages of “tiered” banking systems

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  • Teteryatnikova, Mariya

Abstract

This paper studies the risk and potential impact of system-wide defaults in a tiered banking network, where a small group of head institutions has many credit linkages with other banks, while the majority of banks have only a few links. A network is random and displays a given distribution of the number of banks׳ linkages, known as degree. We model tiering by a negative correlation between degrees of neighboring banks and by a scale-free degree distribution. The main findings of the paper highlight the advantages of tiering. Both the risk of systemic crisis and the potential scope of the crisis are lower in systems with negative correlation of bank degrees than in other types of systems. Similarly, in scale-free networks, the resilience of the system to shocks is increasing with the level of tiering.

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  • Teteryatnikova, Mariya, 2014. "Systemic risk in banking networks: Advantages of “tiered” banking systems," Journal of Economic Dynamics and Control, Elsevier, vol. 47(C), pages 186-210.
  • Handle: RePEc:eee:dyncon:v:47:y:2014:i:c:p:186-210
    DOI: 10.1016/j.jedc.2014.08.007
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    3. Andre R. Neveu, 2018. "A survey of network-based analysis and systemic risk measurement," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(2), pages 241-281, July.
    4. Allouch, Nizar & Jalloul, Maya & Duncan, Alfred, 2023. "Strategic default in financial networks," Games and Economic Behavior, Elsevier, vol. 142(C), pages 941-954.
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    8. Kanas, Angelos & Molyneux, Philip, 2020. "Do measures of systemic risk predict U.S. corporate bond default rates?," International Review of Financial Analysis, Elsevier, vol. 71(C).
    9. Yuri Biondi & Feng Zhou, 2019. "Interbank credit and the money manufacturing process: a systemic perspective on financial stability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(3), pages 437-468, September.
    10. Agathe Sadeghi & Zachary Feinstein, 2024. "Statistical Validation of Contagion Centrality in Financial Networks," Papers 2404.14337, arXiv.org.
    11. Mikhail Stolbov & Daniil Parfenov, 2023. "Credit risk linkages in the international banking network, 2000–2019," Risk Management, Palgrave Macmillan, vol. 25(3), pages 1-38, September.
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    More about this item

    Keywords

    Banking crisis; Contagion; Default; Random network; Disassortative network; Scale-free distribution;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • G01 - Financial Economics - - General - - - Financial Crises
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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