IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2001.04097.html
   My bibliography  Save this paper

Reconstruction of Interbank Network using Ridge Entropy Maximization Model

Author

Listed:
  • Yuichi Ikeda
  • Hidetoshi Takeda

Abstract

We develop a network reconstruction model based on entropy maximization considering the sparsity of networks. We reconstruct the interbank network in Japan from financial data in individual banks' balance sheets using the developed reconstruction model from 2000 to 2016. The observed sparsity of the interbank network is successfully reproduced. We examine the characteristics of the reconstructed interbank network by calculating important network attributes. We obtain the following characteristics, which are consistent with the previously known stylized facts. Although we do not introduce the mechanism to generate the core and peripheral structure, we impose the constraints to consider the sparsity that is no transactions within the same bank category except for major commercial banks, the core and peripheral structure has spontaneously emerged. We identify major nodes in each community using the value of PageRank and degree to examine the changing role of each bank category. The observed changing role of banks is considered a result of the quantitative and qualitative monetary easing policy started by the Bank of Japan in April 2013.

Suggested Citation

  • Yuichi Ikeda & Hidetoshi Takeda, 2020. "Reconstruction of Interbank Network using Ridge Entropy Maximization Model," Papers 2001.04097, arXiv.org, revised Jul 2021.
  • Handle: RePEc:arx:papers:2001.04097
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2001.04097
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yuichi Ikeda & Hiroshi Iyetomi, 2018. "Trade Network Reconstruction and Simulation with Changes in Trade Policy," Papers 1806.00605, arXiv.org.
    2. Eric Monnet & Miklos Vari, 2019. "Liquidity Ratios as Monetary Policy Tools: Some Historical Lessons for Macroprudential Policy," IMF Working Papers 2019/176, International Monetary Fund.
    3. Bergstrand, Jeffrey H, 1985. "The Gravity Equation in International Trade: Some Microeconomic Foundations and Empirical Evidence," The Review of Economics and Statistics, MIT Press, vol. 67(3), pages 474-481, August.
    4. Yuichi Ikeda & Tsutomu Watanabe, 2016. "Who buys what, where: Reconstruction of the international trade flows by commodity and industry," UTokyo Price Project Working Paper Series 071, University of Tokyo, Graduate School of Economics.
    5. Marco Dueñas & Giorgio Fagiolo, 2013. "Modeling the International-Trade Network: a gravity approach," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 155-178, April.
    6. 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.
    7. Upper, Christian, 2011. "Simulation methods to assess the danger of contagion in interbank markets," Journal of Financial Stability, Elsevier, vol. 7(3), pages 111-125, August.
    8. Giulio Cimini & Tiziano Squartini & Diego Garlaschelli & Andrea Gabrielli, 2014. "Systemic risk analysis in reconstructed economic and financial networks," Papers 1411.7613, arXiv.org, revised May 2015.
    9. Yuichi Ikeda & Tsutomu Watanabe, 2016. "Who buys what, where: Reconstruction of the international trade flows by commodity and industry," CARF F-Series CARF-F-393, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yuichi Ikeda & Hiroshi Iyetomi, 2018. "Trade Network Reconstruction and Simulation with Changes in Trade Policy," Papers 1806.00605, arXiv.org.
    2. Yuichi Ikeda & Hiroshi Iyetomi, 2018. "Trade network reconstruction and simulation with changes in trade policy," Evolutionary and Institutional Economics Review, Springer, vol. 15(2), pages 495-513, December.
    3. Marco Bardoscia & Paolo Barucca & Stefano Battiston & Fabio Caccioli & Giulio Cimini & Diego Garlaschelli & Fabio Saracco & Tiziano Squartini & Guido Caldarelli, 2021. "The Physics of Financial Networks," Papers 2103.05623, arXiv.org.
    4. Tiziano Squartini & Guido Caldarelli & Giulio Cimini & Andrea Gabrielli & Diego Garlaschelli, 2018. "Reconstruction methods for networks: the case of economic and financial systems," Papers 1806.06941, arXiv.org.
    5. Wang, Xingxing & Li, Huajiao & Zhu, Depeng & Zhong, Weiqiong & Xing, Wanli & Wang, Anjian, 2021. "Research on global natural graphite trade risk countermeasures based on the maximum entropy principle," Resources Policy, Elsevier, vol. 74(C).
    6. Giulio Cimini & Matteo Serri, 2016. "Entangling Credit and Funding Shocks in Interbank Markets," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-15, August.
    7. Bardoscia, Marco & Barucca, Paolo & Brinley Codd, Adam & Hill, John, 2017. "The decline of solvency contagion risk," Bank of England working papers 662, Bank of England.
    8. Bardoscia, Marco & Barucca, Paolo & Codd, Adam Brinley & Hill, John, 2019. "Forward-looking solvency contagion," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
    9. Giulia Poce & Giulio Cimini & Andrea Gabrielli & Andrea Zaccaria & Giuditta Baldacci & Marco Polito & Mariangela Rizzo & Silvia Sabatini, 2016. "What do central counterparties default funds really cover? A network-based stress test answer," Papers 1611.03782, arXiv.org.
    10. Ramadiah, Amanah & Caccioli, Fabio & Fricke, Daniel, 2020. "Reconstructing and stress testing credit networks," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    11. Alesia Kalbaska & Cesario Mateus, 2019. "From sovereigns to banks: evidence on cross-border contagion," Journal of Banking Regulation, Palgrave Macmillan, vol. 20(1), pages 86-103, March.
    12. Alessandro Ferracci & Giulio Cimini, 2021. "Systemic risk in interbank networks: disentangling balance sheets and network effects," Papers 2109.14360, arXiv.org, revised Sep 2022.
    13. Kanno, Masayasu, 2020. "Interconnectedness and systemic risk in the US CDS market," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    14. Vuillemey, Guillaume & Peltonen, Tuomas A., 2015. "Disentangling the bond–CDS nexus: A stress test model of the CDS market," Economic Modelling, Elsevier, vol. 49(C), pages 32-45.
    15. Ebrahimi Kahou, Mahdi & Lehar, Alfred, 2017. "Macroprudential policy: A review," Journal of Financial Stability, Elsevier, vol. 29(C), pages 92-105.
    16. Fabio Caccioli & Paolo Barucca & Teruyoshi Kobayashi, 2018. "Network models of financial systemic risk: a review," Journal of Computational Social Science, Springer, vol. 1(1), pages 81-114, January.
    17. Petr Teply & Tomas Klinger, 2019. "Agent-based modeling of systemic risk in the European banking sector," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(4), pages 811-833, December.
    18. Sun, Lixin, 2020. "Financial networks and systemic risk in China's banking system," Finance Research Letters, Elsevier, vol. 34(C).
    19. Chen, Bing & Li, Li & Peng, Fei & Anwar, Sajid, 2020. "Risk contagion in the banking network: New evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    20. Giansante, Simone & Manfredi, Sabato & Markose, Sheri, 2023. "Fair immunization and network topology of complex financial ecosystems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 612(C).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2001.04097. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.