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Complex Networks and Banking Systems Supervision

Author

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  • Theophilos Papadimitriou
  • Periklis Gogas
  • Benjamin M. Tabak
Abstract
Comprehensive and thorough supervision of all banking institutions under a Central Bank’s regulatory control has become necessary as recent banking crises show. Promptly identifying bank distress and contagion issues is of great importance to the regulators. This paper proposes a methodology that can be used additionally to the standard methods of bank supervision or the new ones proposed to be implemented. By this, one can reveal the degree of banks’ connectedness and thus identify “core” instead of just “big” banks. Core banks are central in the network in the sense that they are shown to be crucial for network supervision. Core banks can be used as gauges of bank distress over a sub-network and promptly raise a red flag so that the central bank can effectively and swiftly focus on the corresponding neighborhood of financial institutions. In this paper we demonstrated the proposed scheme using as an example the asset returns variable. The method may and should be used with alternative variables as well.

Suggested Citation

  • Theophilos Papadimitriou & Periklis Gogas & Benjamin M. Tabak, 2013. "Complex Networks and Banking Systems Supervision," Working Papers Series 306, Central Bank of Brazil, Research Department.
    • Handle: RePEc:bcb:wpaper:306
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    Cited by:

    1. Rodrigo César de Castro Miranda & Benjamin Miranda Tabak, 2013. "Contagion Risk within Firm-Bank Bivariate Networks," Working Papers Series 322, Central Bank of Brazil, Research Department.
    2. Theophilos Papadimitriou & Periklis Gogas & Georgios Sarantitis, 2016. "Convergence of European Business Cycles: A Complex Networks Approach," Computational Economics, Springer;Society for Computational Economics, vol. 47(2), pages 97-119, February.
    3. Chabot, Miia & Bertrand, Jean-Louis, 2021. "Complexity, interconnectedness and stability: New perspectives applied to the European banking system," Journal of Business Research, Elsevier, vol. 129(C), pages 784-800.
    4. He, Fang & Chen, Xi, 2016. "Credit networks and systemic risk of Chinese local financing platforms: Too central or too big to fail?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 158-170.
    5. Machado, Vicente da Gama & Portugal, Marcelo Savino, 2014. "Measuring inflation persistence in Brazil using a multivariate model," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 68(2), June.
    6. Antonakakis, Nikolaos & Gogas, Periklis & Papadimitriou, Theophilos & Sarantitis, Georgios Antonios, 2016. "International business cycle synchronization since the 1870s: Evidence from a novel network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 286-296.
    7. Kocheturov, A. & Batsyn, M. & Pardalos, P., 2015. "Dynamics of Cluster Structures in Stock Market Networks," Journal of the New Economic Association, New Economic Association, vol. 28(4), pages 12-30.
    8. Guerra, Solange Maria & Silva, Thiago Christiano & Tabak, Benjamin Miranda & de Souza Penaloza, Rodrigo Andrés & de Castro Miranda, Rodrigo César, 2016. "Systemic risk measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 329-342.
    9. Sensoy, Ahmet & Tabak, Benjamin M., 2014. "Dynamic spanning trees in stock market networks: The case of Asia-Pacific," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 387-402.
    10. Zappa, Paola & Vu, Duy Q., 2021. "Markets as networks evolving step by step: Relational Event Models for the interbank market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    11. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    12. 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.
    13. Souza, Sergio R.S. & Tabak, Benjamin M. & Silva, Thiago C. & Guerra, Solange M., 2015. "Insolvency and contagion in the Brazilian interbank market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 431(C), pages 140-151.
    14. 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.
    15. Souza, Sergio Rubens Stancato de & Silva, Thiago Christiano & Tabak, Benjamin Miranda & Guerra, Solange Maria, 2016. "Evaluating systemic risk using bank default probabilities in financial networks," Journal of Economic Dynamics and Control, Elsevier, vol. 66(C), pages 54-75.
    16. Silva, Thiago Christiano & de Souza, Sergio Rubens Stancato & Tabak, Benjamin Miranda, 2016. "Network structure analysis of the Brazilian interbank market," Emerging Markets Review, Elsevier, vol. 26(C), pages 130-152.
    17. de Carvalho, Pablo Jose Campos & Gupta, Aparna, 2018. "A network approach to unravel asset price comovement using minimal dependence structure," Journal of Banking & Finance, Elsevier, vol. 91(C), pages 119-132.
    18. Apergis, Emmanuel & Apergis, Iraklis & Apergis, Nicholas, 2019. "A new macro stress testing approach for financial realignment in the Eurozone," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 52-80.
    19. Barbi, A.Q. & Prataviera, G.A., 2019. "Nonlinear dependencies on Brazilian equity network from mutual information minimum spanning trees," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 876-885.
    20. Thiago C. Silva & Diego R. Amancio & Benjamin M. Tabak, 2020. "Modeling Supply-Chain Networks with Firm-to-Firm Wire Transfers," Papers 2001.06889, arXiv.org, revised Aug 2020.

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