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Directed clustering coefficient as a measure of systemic risk in complex banking networks

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  • Tabak, Benjamin M.
  • Takami, Marcelo
  • Rocha, Jadson M.C.
  • Cajueiro, Daniel O.
  • Souza, Sergio R.S.

Abstract

Recent literature has focused on the study of systemic risk in complex networks. It is clear now, after the crisis of 2008, that the aggregate behavior of the interaction among agents is not straightforward and it is very difficult to predict. Contributing to this debate, this paper shows that the directed clustering coefficient may be used as a measure of systemic risk in complex networks. Furthermore, using data from the Brazilian interbank network, we show that the directed clustering coefficient is negatively correlated with domestic interest rates.

Suggested Citation

  • Tabak, Benjamin M. & Takami, Marcelo & Rocha, Jadson M.C. & Cajueiro, Daniel O. & Souza, Sergio R.S., 2014. "Directed clustering coefficient as a measure of systemic risk in complex banking networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 211-216.
  • Handle: RePEc:eee:phsmap:v:394:y:2014:i:c:p:211-216
    DOI: 10.1016/j.physa.2013.09.010
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    4. Paolo Bartesaghi & Gian Paolo Clemente & Rosanna Grassi, 2021. "Clustering Coefficients in Weighted Undirected Multilayer Networks," Papers 2105.14325, arXiv.org.
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    6. Clemente, G.P. & Grassi, R., 2018. "Directed clustering in weighted networks: A new perspective," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 26-38.
    7. Tinic, Murat & Sensoy, Ahmet & Demir, Muge & Nguyen, Duc Khuong, 2020. "Broker Network Connectivity and the Cross-Section of Expected Stock Returns," MPRA Paper 104719, University Library of Munich, Germany.
    8. Vandermarliere, Benjamin & Karas, Alexei & Ryckebusch, Jan & Schoors, Koen, 2015. "Beyond the power law: Uncovering stylized facts in interbank networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 443-457.
    9. Sensoy, Ahmet & Ozturk, Kevser & Hacihasanoglu, Erk & Tabak, Benjamin M., 2017. "Not all emerging markets are the same: A classification approach with correlation based networks," Journal of Financial Stability, Elsevier, vol. 33(C), pages 163-186.
    10. Rivera-Castro, Miguel A. & Ugolini, Andrea & Arismendi Zambrano, Juan, 2018. "Tail systemic risk and contagion: Evidence from the Brazilian and Latin America banking network," Emerging Markets Review, Elsevier, vol. 35(C), pages 164-189.
    11. 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.
    12. 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).
    13. 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.
    14. Barroso, João Barata Ribeiro Blanco & Silva, Thiago Christiano & Souza, Sergio Rubens Stancato de, 2018. "Identifying systemic risk drivers in financial networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 650-674.
    15. Huang, Chuangxia & Wen, Shigang & Li, Mengge & Wen, Fenghua & Yang, Xin, 2021. "An empirical evaluation of the influential nodes for stock market network: Chinese A-shares case," Finance Research Letters, Elsevier, vol. 38(C).
    16. 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.
    17. Bongini, Paola & Clemente, Gian Paolo & Grassi, Rosanna, 2018. "Interconnectedness, G-SIBs and network dynamics of global banking," Finance Research Letters, Elsevier, vol. 27(C), pages 185-192.
    18. Linardi, Fernando & Diks, Cees & van der Leij, Marco & Lazier, Iuri, 2020. "Dynamic interbank network analysis using latent space models," Journal of Economic Dynamics and Control, Elsevier, vol. 112(C).
    19. Yao, Yanzhen & Li, Jianping & Zhu, Xiaoqian & Wei, Lu, 2017. "Expected default based score for identifying systemically important banks," Economic Modelling, Elsevier, vol. 64(C), pages 589-600.
    20. de Area Leão Pereira, Eder Johnson & da Silva, Marcus Fernandes & Pereira, H.B.B., 2017. "Econophysics: Past and present," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 251-261.
    21. Kosmidou, Kyriaki & Kousenidis, Dimitrios & Ladas, Anestis & Negkakis, Christos, 2017. "Determinants of risk in the banking sector during the European Financial Crisis," Journal of Financial Stability, Elsevier, vol. 33(C), pages 285-296.
    22. Paolo Bartesaghi & Michele Benzi & Gian Paolo Clemente & Rosanna Grassi & Ernesto Estrada, 2019. "Risk-dependent centrality in economic and financial networks," Papers 1907.07908, arXiv.org, revised Apr 2020.
    23. Minoiu, Camelia & Reyes, Javier A., 2013. "A network analysis of global banking: 1978–2010," Journal of Financial Stability, Elsevier, vol. 9(2), pages 168-184.
    24. Wang, Xiaoting & Hou, Siyuan & Shen, Jie, 2021. "Default clustering of the nonfinancial sector and systemic risk: Evidence from China," Economic Modelling, Elsevier, vol. 96(C), pages 196-208.
    25. Li, Yuelei & Hao, Aiting & Zhang, Xiaotao & Xiong, Xiong, 2018. "Network topology and systemic risk in Peer-to-Peer lending market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 118-130.

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