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A Novel Banking Supervision Method Using the Minimum Dominating Set

  • Periklis Gogas
  • Theophilos Papadimitriou
  • Maria-Artemis MatthaiouEmail author
Chapter
Part of the Springer Optimization and Its Applications book series (SOIA, volume 100)

Abstract

The magnitude of the recent financial crisis, which started from the USA and expanded in Europe, changes the perspective on banking supervision. The recent consensus is that to preserve a healthy and stable banking network, the monitoring of all financial institutions should be under a single regulator, the Central Bank. In this paper we study the interrelations of banking institutions under the framework of Complex Networks. Specifically, our goal is to provide an auxiliary early warning system for the banking system’s supervisor that would be used in addition to the existing schemes of control. We employ the Minimum Dominating Set (MDS) methodology to reveal the most strategically important banks of the banking network and use them as alarm triggers. By monitoring the MDS subset the regulators can have an overview of the whole network. Our dataset is formed from the 200 largest American banks and we examine their interconnection through their total deposits. The MDS concept is applied for the first time in this setting and the results show that it may be an essential supplementary tool to the arsenal of a Central Bank.

Keywords

Central Bank Banking System Systemic Risk Total Deposit Complete Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Allen, F., Gale, D.: Financial contagion. J. Polit. Econ. 108, 1–33 (2000)Google Scholar
  2. 2.
    Angelini, P., Maresca, G., Russo, D.: Systemic risk in the netting system. J. Bank. Finance 20, 853–868 (1996)CrossRefGoogle Scholar
  3. 3.
    Blinder, A.S.: How central should the Central Bank be. CEPS WP198, 1–20 (2010)Google Scholar
  4. 4.
    Boss, M., Elsinger, H., Summer, M., Thurner, S.: Network topology of the interbank market. Quant. Finance 4, 677–684 (2004)CrossRefGoogle Scholar
  5. 5.
    Boyer, P.C., Ponce, J.: Regulatory capture and Banking supervision reform. J. Financ. Stabil. 8, 206–217 (2012)CrossRefGoogle Scholar
  6. 6.
    Chan-Lau, J.A.: Balance sheet network analysis of too-connected-to-fail risk in global and domestic banking systems. IMF WP107, 1–25 (2010)Google Scholar
  7. 7.
    Gai, P., Kapadia, S.: Contagion in financial networks. Proc. Roy. Soc. A Math. Phys. Eng. Sci. 466, 2401–2423 (2010)MathSciNetCrossRefzbMATHGoogle Scholar
  8. 8.
    Inaoka, H., Takayasu, H., Shimizu, T. Ninomiya, T., Taniguchi, K.: Self-similarity of banking network. Phys. A 339, 621–634 (2004)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Iori, G., Masi, G.D., Precup, O.V., Gabbi, G., Caldarelli, G.: A network analysis of the Italian overnight money market. J. Econ. Dynam. Contr. 32, 259–278 (2008)CrossRefzbMATHGoogle Scholar
  10. 10.
    Leitner, Y.: Financial networks: contagion, commitment and private sector bailouts. J. Finance. 60, 925–953 (2005)CrossRefGoogle Scholar
  11. 11.
    Minoiu, C., Reyes, J.A.: A networks analysis of global banking: 1978–2009. IMF WP74, 11–41 (2011)Google Scholar
  12. 12.
    Papadimitriou, T., Gogas, P., Tabak, B.M.: Complex networks and banking systems supervision. Phys. A Stat. Mech. Appl. 392, 4429–4434 (2013)CrossRefGoogle Scholar
  13. 13.
    Schleich, J., Thi, H., Bouvry, P.: Solving the minimum M-dominating set problem by a continuous optimization approach based on DC programming and DCA. J. Comb. Optim. 24, 397–412 (2011)CrossRefGoogle Scholar
  14. 14.
    Steen, M.: Graph Theory and Complex Networks: An Introduction, vol. 9081540610, 1–300 (2010)Google Scholar
  15. 15.
    Tabak, B.M., Takami, M., Rocha, J.M.C., Cajuero, D.O.: Directed clustering coefficient as a measure of systemic risk in complex networks. Working paper of Banco Central do Brazil, vol. 249, 3–17 (2011)Google Scholar
  16. 16.
    Thurner, S., Hanel, R., Pichler, S.: Risk trading, network topology and banking regulation. Quant. Finance. 3, 306–319 (2010)MathSciNetCrossRefGoogle Scholar
  17. 17.
    Vives, X.: Central Banks and Supervision. Challenges for Modern Central Banking, pp. 95–113. Klumer Academic, Boston (2001)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Periklis Gogas
    • 1
  • Theophilos Papadimitriou
    • 1
  • Maria-Artemis Matthaiou
    • 1
    Email author
  1. 1.Department of EconomicsDemocritus University of ThraceKomotini, RodopiGreece

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