Advertisement

The Research of Bankruptcies’ Succession by Systemic Risk Index

  • Morito HashimotoEmail author
  • Setsuya Kurahashi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10247)

Abstract

To lower the risk of a chain reaction of bank failures, active studies of fund transaction networks that are related to systemic risks have been conducted globally, and they are centered in Europe. In this study, we propose a new systemic risk index that reduces the risk of a chain reaction of failures at minimum cost by building a model of interbank fund transaction networks. This model’s structure has as its basis on the Erdos-Renyi network and considers the network’s characteristics. Our verification, using an agent-based modeling method, confirms that financial assistance given to stop chain reaction failures could increase the possibility of a chain reaction and that the systemic risk index can be used as a reference to determine financial institutions that should be given financial assistance.

Keywords

Agent-based modeling Systemic risk Network theory Interbank transaction 

References

  1. 1.
    Acharya, V., Engle, R., Richardson, M.: Capital shortfall: a new approach to ranking and regulating systemic risks. Am. Econ. Rev. 102(3), 59–64 (2012)CrossRefGoogle Scholar
  2. 2.
    Benoit, S., Colliard, J.-E., Hurlin, C., Perignon, C.: Where the risks lie: a survey on systemic risk. HEC Paris Research Paper (2015)Google Scholar
  3. 3.
    Eisenberg, L., Noe, T.H.: Systemic risk in financial systems. Manag. Sci. 47(2), 236–249 (2001)CrossRefzbMATHGoogle Scholar
  4. 4.
    Gai, P., Kapadia, S.: Contagion in financial networks. Bank Engl. Q. Bull. 50(2), 124 (2010)zbMATHGoogle Scholar
  5. 5.
    May, R.M., Arinaminpathy, N.: Systemic risk: the dynamics of model banking systems. J. Roy. Soc. Interface/Roy. Soc. 7(46), 823–838 (2010)CrossRefGoogle Scholar
  6. 6.
    Nier, E., Yang, J., Yorulmazer, T., Alentorn, A.: Network models and financial stability. J. Econ. Dyn. Control 31(6), 2033–2060 (2007)CrossRefzbMATHGoogle Scholar
  7. 7.
    Kei, I., Yutaka, S.: Funds trading network of the call market. Stud. Financ. 27, 47–99 (2008)Google Scholar
  8. 8.
    Norio, K., Naoki, M.: Complex Network. Kindai Kagaku-Sya, Tokyo (2010)Google Scholar
  9. 9.
    Cifuentes, R., Ferrucci, G., Shin, H.S.: Liquidity risk and contagion. J. Eur. Econ. Assoc. 3(2–3), 556–566 (2005)CrossRefGoogle Scholar
  10. 10.
    Dias, A., Campos, P., Garrido, P.: An agent based propagation model of bank failures. In: Amblard, F., Miguel, F.J., Blanchet, A., Gaudou, B. (eds.) Advances in Artificial Economics. LNEMS, vol. 676, pp. 119–130. Springer, Cham (2015). doi: 10.1007/978-3-319-09578-3_10 Google Scholar
  11. 11.
    Hyun, S.S.: Risk and Liquidity. Oxford University Press Inc., Oxford (2010)Google Scholar
  12. 12.
    Montagna, M., Lux, T.: Hubs and resilience: towards more realistic models of the interbank markets. Some Recent Developments, Banking Integration and Financial Crisis (2015)Google Scholar
  13. 13.
    Takamasa, K., Masaaki, K., Takashi, Y., Hiroshi, T., Takao, T.: Analysis of the influences of central bank financing on operative collapses of financial institutions using agent-based simulation. In: 2016 IEEE 40th Annual Computer Software and Applications Conference (COMPSAC), pp. 95–104. IEEE (2016)Google Scholar
  14. 14.
    Maeno, Y., Morinaga, S., Matsushima, H., Amaya, K.: Risk of the collapse of a bank credit network. JSAI 27(6), 338–345 (2012)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Business ScienceTsukuba UniversityTokyoJapan

Personalised recommendations