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Disentangling bipartite and core-periphery structure in financial networks

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  • Barucca, Paolo
  • Lillo, Fabrizio
Abstract
A growing number of systems are represented as networks whose architecture conveys significant information and determines many of their properties. Examples of network architecture include modular, bipartite, and core-periphery structures. However inferring the network structure is a non trivial task and can depend sometimes on the chosen null model. Here we propose a method for classifying network structures and ranking its nodes in a statistically well-grounded fashion. The method is based on the use of Belief Propagation for learning through Entropy Maximization on both the Stochastic Block Model (SBM) and the degree-corrected Stochastic Block Model (dcSBM). As a specific application we show how the combined use of the two ensembles—SBM and dcSBM—allows to disentangle the bipartite and the core-periphery structure in the case of the e-MID interbank network. Specifically we find that, taking into account the degree, this interbank network is better described by a bipartite structure, while using the SBM the core-periphery structure emerges only when data are aggregated for more than a week.

Suggested Citation

  • Barucca, Paolo & Lillo, Fabrizio, 2016. "Disentangling bipartite and core-periphery structure in financial networks," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 244-253.
    • Handle: RePEc:eee:chsofr:v:88:y:2016:i:c:p:244-253
    DOI: 10.1016/j.chaos.2016.02.004
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    References listed on IDEAS

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    Cited by:

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    6. 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.
    7. Duarte Queirós, Sílvio M. & Anteneodo, Celia, 2016. "Complexity in quantitative finance and economics," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 1-2.
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    10. Clemente, G.P. & Grassi, R., 2018. "Directed clustering in weighted networks: A new perspective," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 26-38.
    11. Chen, Lei & Kou, Yingxin & Li, Zhanwu & Xu, An & Chang, Yizhe, 2018. "Relationships between Perron–Frobenius eigenvalue and measurements of loops in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 153-163.
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    13. 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.
    14. Barucca, Paolo, 2020. "Spectral density of equitable core–periphery graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    15. Yanquen, Eduardo & Livan, Giacomo & Montañez-Enriquez, Ricardo & Martinez-Jaramillo, Serafin, 2022. "Measuring systemic risk for bank credit networks: A multilayer approach," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 3(2).
    16. Hric, Darko & Kaski, Kimmo & Kivelä, Mikko, 2018. "Stochastic block model reveals maps of citation patterns and their evolution in time," Journal of Informetrics, Elsevier, vol. 12(3), pages 757-783.
    17. Sadamori Kojaku & Giulio Cimini & Guido Caldarelli & Naoki Masuda, 2018. "Structural changes in the interbank market across the financial crisis from multiple core-periphery analysis," Papers 1802.05139, arXiv.org.
    18. Tiziano Squartini & Guido Caldarelli & Giulio Cimini & Andrea Gabrielli & Diego Garlaschelli, 2018. "Reconstruction methods for networks: the case of economic and financial systems," Papers 1806.06941, arXiv.org.
    19. Kotlicki, Artur & Austin, Andrea & Humphry, David & Burnett, Hanna & Ridgill, Philip & Smith, Sam, 2023. "Network analysis of the UK reinsurance market," Bank of England working papers 1000, Bank of England.
    20. Téllez-León, Isela-Elizabeth & Martínez-Jaramillo, Serafín & O. L. Escobar-Farfán, Luis & Hochreiter, Ronald, 2021. "How are network centrality metrics related to interest rates in the Mexican secured and unsecured interbank markets?," Journal of Financial Stability, Elsevier, vol. 55(C).
    21. Carlo Campajola & Raffaele Cristodaro & Francesco Maria De Collibus & Tao Yan & Nicolo' Vallarano & Claudio J. Tessone, 2022. "The Evolution Of Centralisation on Cryptocurrency Platforms," Papers 2206.05081, arXiv.org, revised May 2023.
    22. Li, Jiang-Cheng & Leng, Na & Zhong, Guang-Yan & Wei, Yu & Peng, Jia-Sheng, 2020. "Safe marginal time of crude oil price via escape problem of econophysics," Chaos, Solitons & Fractals, Elsevier, vol. 133(C).
    23. Thorben Funke & Till Becker, 2019. "Stochastic block models: A comparison of variants and inference methods," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-40, April.
    24. Adão, Luiz F.S. & Silveira, Douglas & Ely, Regis A. & Cajueiro, Daniel O., 2022. "The impacts of interest rates on banks’ loan portfolio risk-taking," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    25. Fabrizio Lillo & Giorgio Rizzini, 2024. "Modelling shock propagation and resilience in financial temporal networks," Papers 2407.09340, arXiv.org.

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