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Self-similarity of banking network

Author

Listed:
  • Inaoka, Hajime
  • Takayasu, Hideki
  • Shimizu, Tokiko
  • Ninomiya, Takuto
  • Taniguchi, Ken

Abstract

We analyzed a network structure formed by monetary transactions between financial institutions. We present a procedure to extract a network structure from a set of records of transactions. The extracted network has self-similarity described by a power-law degree distribution. We also introduce a propagation function to describe the self-similarity. A model of network formation based on a mean-field type interaction is proposed to reproduce the self-similarity of the network.

Suggested Citation

  • Inaoka, Hajime & Takayasu, Hideki & Shimizu, Tokiko & Ninomiya, Takuto & Taniguchi, Ken, 2004. "Self-similarity of banking network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(3), pages 621-634.
    • Handle: RePEc:eee:phsmap:v:339:y:2004:i:3:p:621-634
    DOI: 10.1016/j.physa.2004.03.011
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    Cited by:

    1. Hernández, Juan M. & González-Martel, Christian, 2017. "An evolving model for the lodging-service network in a tourism destination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 296-307.
    2. Gogas, Periklis & Papadimitriou, Theophilos & Matthaiou, Maria-Artemis, 2016. "Bank supervision using the Threshold-Minimum Dominating Set," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 23-35.
    3. Yichen Zhou & Honggang Li, 2019. "Asset diversification and systemic risk in the financial system," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(2), pages 247-272, June.
    4. Periklis Gogas & Theophilos Papadimitriou & Maria-Artemis Matthaiou, 2014. "A Novel Banking Supervision Method Using the Minimum Dominating Set," Springer Optimization and Its Applications, in: Valery A. Kalyagin & Panos M. Pardalos & Themistocles M. Rassias (ed.), Network Models in Economics and Finance, edition 127, pages 277-286, Springer.
    5. Toshiyuki Sakiyama & Tetsuya Yamada, 2016. "Market Liquidity and Systemic Risk in Government Bond Markets: A Network Analysis and Agent-Based Model Approach," IMES Discussion Paper Series 16-E-13, Institute for Monetary and Economic Studies, Bank of Japan.
    6. Qianqian Gao & Hong Fan, 2020. "Macroprudential regulation for a dynamic Chinese banking system with a scale-free network," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(3), pages 579-611, July.
    7. Yoshiharu Maeno & Kenji Nishiguchi & Satoshi Morinaga & Hirokazu Matsushima, 2014. "Impact of credit default swaps on financial contagion," Papers 1411.1356, arXiv.org.
    8. Yoshiharu Maeno & Kenji Nishiguchi & Satoshi Morinaga & Hirokazu Matsushima, 2012. "Optimal portfolio for a robust financial system," Papers 1211.5235, arXiv.org, revised Feb 2013.
    9. Mitja Steinbacher & Timotej Jagrič, 2020. "Interbank rules during economic declines: Can banks safeguard capital base?," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(2), pages 471-499, April.
    10. Ou, Ruiqiu & Yang, Jianmei, 2012. "On structural properties of scale-free networks with finite size," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 887-894.
    11. Anca Gheorghiu & Ion Spanulescu, 2012. "An Econophysics Model for the Migration Phenomena," Papers 1202.0996, arXiv.org.
    12. He, Jianmin & Sui, Xin & Li, Shouwei, 2016. "An endogenous model of the credit network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 441(C), pages 1-14.
    13. Xu, Tao & He, Jianmin & Li, Shouwei, 2016. "A dynamic network model for interbank market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 131-138.

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    Keywords

    Banking; Network; Mean-field;
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