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

Listed author(s):
  • Luu, Duc Thi
  • Lux, Thomas
  • Yanovski, Boyan
Registered author(s):

    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.

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    File URL: https://www.econstor.eu/bitstream/10419/156399/1/88320620X.pdf
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    Paper provided by Christian-Albrechts-University of Kiel, Department of Economics in its series Economics Working Papers with number 2017-02.

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    Date of creation: 2017
    Handle: RePEc:zbw:cauewp:201702
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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. 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.
    3. Tiziano Squartini & Giorgio Fagiolo & Diego Garlaschelli, 2011. "Randomizing world trade. II. A weighted network analysis," Papers 1103.1249, arXiv.org, revised Nov 2011.
    4. Tiziano Squartini & Giorgio Fagiolo & Diego Garlaschelli, 2011. "Randomizing world trade. I. A binary network analysis," Papers 1103.1243, arXiv.org, revised Nov 2011.
    5. 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.
    6. 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.
    7. 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.
    8. 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, 05.
    9. D. Garlaschelli & M. I. Loffredo, 2004. "Fitness-dependent topological properties of the World Trade Web," Papers cond-mat/0403051, arXiv.org, revised Oct 2004.
    10. 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.
    11. 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.
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