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Structural correlations in the Italian overnight money market: An analysis based on network configuration models

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  • Luu, Duc Thi
  • Lux, Thomas
  • Yanovski, Boyan

Abstract

We study the structural correlations in the Italian overnight money market over the period 1999-2010. We show that the structural correlations vary across different versions of the network. Moreover, we employ different configuration models and examine whether higher-level characteristics of the observed network can be statistically reconstructed by maximizing the entropy of a randomized ensemble of networks restricted only by the lower-order features of the observed network. We find that often many of the high order correlations in the observed network can be considered emergent from the information embedded in the degree sequence in the binary version and in both the degree and strength sequences in the weighted version. However, this information is not enough to allow the models to account for all the patterns in the observed higher order structural correlations. In particular, one of the main features of the observed network that remains unexplained is the abnormally high level of weighted clustering in the years preceding the crisis, i.e. the huge increase in various indirect exposures generated via more intensive interbank credit links.

Suggested Citation

  • 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.
    • Handle: RePEc:zbw:cauewp:201702
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    References listed on IDEAS

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    1. D. Garlaschelli & T. Di Matteo & T. Aste & G. Caldarelli & M. I. Loffredo, 2007. "Interplay between topology and dynamics in the World Trade Web," Papers physics/0701030, arXiv.org.
    2. Zhang Bin & Horvath Steve, 2005. "A General Framework for Weighted Gene Co-Expression Network Analysis," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 4(1), pages 1-45, August.
    3. Tiziano Squartini & Giorgio Fagiolo & Diego Garlaschelli, 2011. "Randomizing world trade. I. A binary network analysis," Papers 1103.1243, arXiv.org, revised Nov 2011.
    4. 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.
    5. 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.
    6. 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.
    7. Daniel Fricke & Thomas Lux, 2015. "On the distribution of links in the interbank network: evidence from the e-MID overnight money market," Empirical Economics, Springer, vol. 49(4), pages 1463-1495, December.
    8. Giulio Cimini & Tiziano Squartini & Diego Garlaschelli & Andrea Gabrielli, 2014. "Systemic risk analysis in reconstructed economic and financial networks," Papers 1411.7613, arXiv.org, revised May 2015.
    9. Tiziano Squartini & Giorgio Fagiolo & Diego Garlaschelli, 2011. "Randomizing world trade. II. A weighted network analysis," Papers 1103.1249, arXiv.org, revised Nov 2011.
    10. V. Zlatic & G. Bianconi & A. Díaz-Guilera & D. Garlaschelli & F. Rao & G. Caldarelli, 2009. "On the rich-club effect in dense and weighted networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 67(3), pages 271-275, February.
    11. Maslov, Sergei & Sneppen, Kim & Zaliznyak, Alexei, 2004. "Detection of topological patterns in complex networks: correlation profile of the internet," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 529-540.
    12. Tiziano Squartini & Iman van Lelyveld & Diego Garlaschelli, 2013. "Early-warning signals of topological collapse in interbank networks," Papers 1302.2063, arXiv.org, revised Nov 2013.
    13. D. Garlaschelli & T. Di Matteo & T. Aste & G. Caldarelli & M. I. Loffredo, 2007. "Interplay between topology and dynamics in the World Trade Web," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 57(2), pages 159-164, May.
    14. Holme, Petter & Min Park, Sung & Kim, Beom Jun & Edling, Christofer R., 2007. "Korean university life in a network perspective: Dynamics of a large affiliation network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 821-830.
    15. 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).
    16. Fricke, Daniel, 2012. "Trading strategies in the overnight money market: Correlations and clustering on the e-MID trading platform," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(24), pages 6528-6542.
    17. D. Garlaschelli & M. I. Loffredo, 2004. "Fitness-dependent topological properties of the World Trade Web," Papers cond-mat/0403051, arXiv.org, revised Oct 2004.
    18. 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).
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    Cited by:

    1. Bartesaghi, Paolo & Clemente, Gian Paolo & Grassi, Rosanna & Luu, Duc Thi, 2022. "The multilayer architecture of the global input-output network and its properties," Journal of Economic Behavior & Organization, Elsevier, vol. 204(C), pages 304-341.
    2. 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.

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    More about this item

    Keywords

    Interbank Network; Structural Correlations; Clustering Coefficients; Configuration Models; Network Reconstruction;
    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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