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On assortative and disassortative mixing in scale-free networks: The case of interbank credit networks

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  • Fricke, Daniel
  • Finger, Karl
  • Lux, Thomas

Abstract

Networks constructed from credit relationships in the interbank market have been found to exhibit disassortative mixing together with a scale-free degree distribution, in contrast to most social networks that are assortative and not necessarily scale-free. This provokes the question whether generating mechanisms for scale-free networks have enough flexibility to generate both assortative and disassortative structures depending on their parametrization. Using Monte-Carlo simulations, we show that scale-free networks with a small tail exponent tend to be disassortative. However, the simulations indicate also that the level of disassortativity is sensitive to changes in the scaling exponent and the density. A given combination of disassortativity, scaling of the degree distribution, and density in an empirical data set, might be hard or impossible to obtain from any of the known generating mechanisms for scale-free networks.

Suggested Citation

  • Fricke, Daniel & Finger, Karl & Lux, Thomas, 2013. "On assortative and disassortative mixing in scale-free networks: The case of interbank credit networks," Kiel Working Papers 1830, Kiel Institute for the World Economy (IfW Kiel).
  • Handle: RePEc:zbw:ifwkwp:1830
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    References listed on IDEAS

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    1. de Masi, G. & Iori, G. & Caldarelli, G., 2006. "A fitness model for the Italian interbank money market," Working Papers 06/08, Department of Economics, City University London.
    2. Karl Finger & Daniel Fricke & Thomas Lux, 2013. "Network analysis of the e-MID overnight money market: the informational value of different aggregation levels for intrinsic dynamic processes," Computational Management Science, Springer, vol. 10(2), pages 187-211, June.
    3. Michael D. König & Claudio J. Tessone & Yves Zenou, 2010. "From Assortative To Dissortative Networks: The Role Of Capacity Constraints," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 13(04), pages 483-499.
    4. Craig, Ben & von Peter, Goetz, 2014. "Interbank tiering and money center banks," Journal of Financial Intermediation, Elsevier, vol. 23(3), pages 322-347.
    5. Beaupain, Renaud & Durré, Alain, 2013. "Central bank reserves and interbank market liquidity in the euro area," Journal of Financial Intermediation, Elsevier, vol. 22(2), pages 259-284.
    6. Fricke, Daniel & Lux, Thomas, 2012. "Core-periphery structure in the overnight money market: Evidence from the e-MID trading platform," Kiel Working Papers 1759, Kiel Institute for the World Economy (IfW Kiel).
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    Cited by:

    1. Feroldi Valentina & Gaffeo Edoardo, 2014. "At the Core of the International Financial System," Global Economy Journal, De Gruyter, vol. 14(2), pages 1-26, April.
    2. Daniel Grigat & Fabio Caccioli, 2017. "Reverse stress testing interbank networks," Papers 1702.08744, arXiv.org, revised Mar 2017.
    3. Paolo Barucca & Fabrizio Lillo, 2018. "The organization of the interbank network and how ECB unconventional measures affected the e-MID overnight market," Computational Management Science, Springer, vol. 15(1), pages 33-53, January.
    4. Joseph, Andreas & Osbat, Chiara, 2016. "How you export matters: the disassortative structure of international trade," Working Paper Series 1958, European Central Bank.
    5. Yangbo Song & Mihaela Schaar, 2015. "Dynamic network formation with incomplete information," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 59(2), pages 301-331, June.
    6. L. Bargigli & G. di Iasio & L. Infante & F. Lillo & F. Pierobon, 2015. "The multiplex structure of interbank networks," Quantitative Finance, Taylor & Francis Journals, vol. 15(4), pages 673-691, April.
    7. Lux, Thomas, 2014. "Emergence of a Core-Periphery Structure in a Simple Dynamic Model of the Interbank Market," FinMaP-Working Papers 3, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    8. Barucca, Paolo & Lillo, Fabrizio, 2016. "Disentangling bipartite and core-periphery structure in financial networks," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 244-253.
    9. Berndsen, Ron J. & León, Carlos & Renneboog, Luc, 2018. "Financial stability in networks of financial institutions and market infrastructures," Journal of Financial Stability, Elsevier, vol. 35(C), pages 120-135.
    10. Luu, Duc Thi & Lux, Thomas & Yanovski, Boyan, 2017. "Structural correlations in the Italian overnight money market: An analysis based on network configuration models," Economics Working Papers 2017-02, Christian-Albrechts-University of Kiel, Department of Economics.
    11. Schrader, Klaus & Bencek, David & Laaser, Claus-Friedrich, 2013. "IfW-Krisencheck: Alles wieder gut in Griechenland?," Kiel Discussion Papers 522/523, Kiel Institute for the World Economy (IfW Kiel).
    12. Paolo Barucca & Fabrizio Lillo, 2015. "The organization of the interbank network and how ECB unconventional measures affected the e-MID overnight market," Papers 1511.08068, arXiv.org, revised Sep 2017.
    13. Lux, Thomas, 2016. "Network effects and systemic risk in the banking sector," FinMaP-Working Papers 62, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    14. Lux, Thomas, 2014. "Emergence of a core-periphery structure in a simple dynamic model of the interbank market," Kiel Working Papers 1917, Kiel Institute for the World Economy (IfW Kiel).
    15. Maria Rosa Borges & Lauriano Ulica & Mariya Gubareva, 2020. "Systemic risk in the Angolan interbank payment system – a network approach," Applied Economics, Taylor & Francis Journals, vol. 52(45), pages 4900-4912, September.
    16. Paolo Barucca & Fabrizio Lillo, 2015. "Disentangling bipartite and core-periphery structure in financial networks," Papers 1511.08830, arXiv.org.

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    More about this item

    Keywords

    interbank market; network models; scale-free networks; powerlaw;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G01 - Financial Economics - - General - - - Financial Crises
    • E42 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Monetary Sytsems; Standards; Regimes; Government and the Monetary System

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