IDEAS home Printed from https://ideas.repec.org/p/koe/wpaper/1502.html
   My bibliography  Save this paper

Cascades in multiplex financial networks with debts of different seniority

Author

Listed:
  • Charles D. Brummitt

    (Center for the Management of Systemic Risk, Columbia University)

  • Teruyoshi Kobayashi

    () (Graduate School of Economics, Kobe University)

Abstract

The seniority of debt, which determines the order in which a bankrupt institution repays its debts, is an important and sometimes contentious feature of financial crises, yet its impact on system-wide stability is not well understood. We capture seniority of debt in a multiplex network, a graph of nodes connected by multiple types of edges. Here, an edge between banks denotes a debt contract of a certain level of seniority. Next we study cascading default. There exist multiple kinds of bankruptcy, indexed by the highest level of seniority at which a bank cannot repay all its debts. Self-interested banks would prefer that all their loans be made at the most senior level. However, mixing debts of different seniority levels makes the system more stable, in that it shrinks the set of network densities for which bankruptcies spread widely. We compute the optimal ratio of senior to junior debts, which we call the optimal seniority ratio, for two uncorrelated Erdos-Renyi networks. If institutions erode their buffer against insolvency, then this optimal seniority ratio rises; in other words, if default thresholds fall, then more loans should be senior. We generalize the analytical results to arbitrarily many levels of seniority and to heavy-tailed degree distributions.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Charles D. Brummitt & Teruyoshi Kobayashi, 2015. "Cascades in multiplex financial networks with debts of different seniority," Discussion Papers 1502, Graduate School of Economics, Kobe University.
  • Handle: RePEc:koe:wpaper:1502
    as

    Download full text from publisher

    File URL: http://www.econ.kobe-u.ac.jp/RePEc/koe/wpaper/2015/1502.pdf
    Download Restriction: no

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li, Shouwei & Liu, Yifu & Wu, Chaoqun, 2020. "Systemic risk in bank-firm multiplex networks," Finance Research Letters, Elsevier, vol. 33(C).
    2. 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.
    3. Kobayashi, Teruyoshi & Takaguchi, Taro, 2018. "Identifying relationship lending in the interbank market: A network approach," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 20-36.
    4. X. Zhang & L. D. Valdez & H. E. Stanley & L. A. Braunstein, 2019. "Modeling Risk Contagion in the Venture Capital Market: A Multilayer Network Approach," Complexity, Hindawi, vol. 2019, pages 1-11, December.
    5. Teruyoshi Kobayashi & Anna Sapienza & Emilio Ferrara, 2018. "Extracting the multi-timescale activity patterns of online financial markets," Discussion Papers 1809, Graduate School of Economics, Kobe University.
    6. Teruyoshi Kobayashi & Taro Takaguchi, 2017. "Significant ties: Identifying relationship lending in temporal interbank networks," Discussion Papers 1717, Graduate School of Economics, Kobe University.
    7. Wang, Jianwei & Cai, Lin & Xu, Bo & Li, Peng & Sun, Enhui & Zhu, Zhiguo, 2016. "Out of control: Fluctuation of cascading dynamics in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1231-1243.
    8. Teruyoshi Kobayashi, 2015. "Trend-driven information cascades on random networks," Discussion Papers 1529, Graduate School of Economics, Kobe University.
    9. De Caux, Robert & McGroarty, Frank & Brede, Markus, 2017. "The evolution of risk and bailout strategy in banking systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 109-118.

    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:koe:wpaper:1502. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Kimiaki Shirahama) The email address of this maintainer does not seem to be valid anymore. Please ask Kimiaki Shirahama to update the entry or send us the correct email address. General contact details of provider: http://edirc.repec.org/data/fekobjp.html .

    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.

    We have no references for this item. You can help adding them by using 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.