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A network model of the interbank market

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  • Li, Shouwei
  • He, Jianmin
  • Zhuang, Yaming
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    Abstract

    This work introduces a network model of an interbank market based on interbank credit lending relationships. It generates some network features identified through empirical analysis. The critical issue to construct an interbank network is to decide the edges among banks, which is realized in this paper based on the interbank’s degree of trust. Through simulation analysis of the interbank network model, some typical structural features are identified in our interbank network, which are also proved to exist in real interbank networks. They are namely, a low clustering coefficient and a relatively short average path length, community structures, and a two-power-law distribution of out-degree and in-degree.

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    Bibliographic Info

    Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

    Volume (Year): 389 (2010)
    Issue (Month): 24 ()
    Pages: 5587-5593

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    Handle: RePEc:eee:phsmap:v:389:y:2010:i:24:p:5587-5593

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    Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

    Related research

    Keywords: Interbank market; Clustering coefficient; Average path length; Community structure; Degree distribution;

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    Cited by:
    1. Papadimitriou, Theophilos & Gogas, Periklis & Tabak, Benjamin M., 2013. "Complex networks and banking systems supervision," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4429-4434.
    2. Sokolov, Andrey & Webster, Rachel & Melatos, Andrew & Kieu, Tien, 2012. "Loan and nonloan flows in the Australian interbank network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(9), pages 2867-2882.

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