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Network-based risk measurements for interbank systems

Author

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  • Yongli Li
  • Guanghe Liu
  • Paolo Pin

Abstract

This paper focuses on evaluating the systemic risk in interbank networks, proposing a series of measurements: risk distance, risk degree and m-order risk degree. The proposed measurements are formally proven to have good basic and extended properties that are able to reflect the effect of bank size, liability size, liability distribution, and the discount factor on the default risk, not only of a single bank, but also of the entire system. Additionally, the abovementioned properties and the relationship between risk distance and financial contagion indicate the rationality embodied in the proposed measurements. This paper also provides some implications on how to decrease or prevent the systemic risk in an interbank system.

Suggested Citation

  • 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.
    • Handle: RePEc:plo:pone00:0200209
    DOI: 10.1371/journal.pone.0200209
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    Cited by:

    1. Deng, Yang & Zhang, Ziqing & Zhu, Li, 2021. "A model-based index for systemic risk contribution measurement in financial networks," Economic Modelling, Elsevier, vol. 95(C), pages 35-48.
    2. Feinstein, Zachary & Sojmark, Andreas, 2021. "Short communication: dynamic default contagion in heterogeneous interbank systems," LSE Research Online Documents on Economics 123789, London School of Economics and Political Science, LSE Library.
    3. Yaya Li & Yongtao Peng & Jianqiang Luo & Yihan Cheng & Eleonora Veglianti, 2019. "Spatial-temporal variation characteristics and evolution of the global industrial robot trade: A complex network analysis," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-14, September.
    4. Zachary Feinstein & Andreas Sojmark, 2020. "Dynamic Default Contagion in Heterogeneous Interbank Systems," Papers 2010.15254, arXiv.org, revised Jul 2021.
    5. Tabak, Benjamin Miranda & Silva, Thiago Christiano & Fiche, Marcelo Estrela & Braz, Tércio, 2021. "Citation likelihood analysis of the interbank financial networks literature: A machine learning and bibliometric approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).

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