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The microstructure of the money market before and after the financial crisis: a network perspective

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Abstract

This paper provides an in depth microstructure analysis of the euro money market by taking a network perspective. Banks are the nodes of the networks; unsecured overnight loans form the links connecting the nodes. Daily interbank networks verify the same stylised facts documented for many real complex systems: they are highly sparse, far from being complete, exhibit the small world property and a power-law distribution of degree (the number of counterparties each bank establishes credit relationships with). On the other hand, the tendency of banks to cluster, i.e. to form groups where ties are relatively denser, is much lower than in other real networks. The time patterns of some network statistics provide interesting insights into the evolution of the potential for financial contagion; the partition of the network into smaller connected subnetworks documents a move against market integration; heterogeneous developments across banks of different size offer insights into banks’ behaviour. An analysis of banks’ prominence in the market is undertaken using centrality measures: the various indicators suggest that the biggest banks are also the most connected before the onset of the crisis; however, medium/small and very small banks’ centralities increase progressively after August 2007 as these banks increase their “influence” as liquidity providers. The rich set of measures described in this paper represents a key input for future research.

Suggested Citation

  • Silvia Gabrieli, 2011. "The microstructure of the money market before and after the financial crisis: a network perspective," CEIS Research Paper 181, Tor Vergata University, CEIS, revised 19 Jan 2011.
  • Handle: RePEc:rtv:ceisrp:181
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    1. Soramäki, Kimmo & Bech, Morten L. & Arnold, Jeffrey & Glass, Robert J. & Beyeler, Walter E., 2007. "The topology of interbank payment flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(1), pages 317-333.
    2. Ethan Cohen-Cole & Andrei Kirilenko & Eleonora Patacchini, 2010. "Are Networks Priced? Network Topology and Order Trading Strategies in High Liquidity Markets," EIEF Working Papers Series 1011, Einaudi Institute for Economics and Finance (EIEF), revised Apr 2010.
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    Cited by:

    1. Grzegorz Hałaj & Christoffer Kok, 2013. "Assessing interbank contagion using simulated networks," Computational Management Science, Springer, vol. 10(2), pages 157-186, June.
    2. Marco Pelliccia, 2013. "Ambiguous Networks," Birkbeck Working Papers in Economics and Finance 1303, Birkbeck, Department of Economics, Mathematics & Statistics.
    3. Silvio Schumacher, 2016. "Networks and lending conditions: Empirical evidence from the Swiss franc money markets," Working Papers 2016-12, Swiss National Bank.
    4. repec:wsi:acsxxx:v:15:y:2012:i:supp0:n:s0219525912500865 is not listed on IDEAS
    5. Galina Hale & Tümer Kapan & Camelia Minoiu, 2016. "Crisis Transmission in the Global Banking Network," IMF Working Papers 16/91, International Monetary Fund.
    6. Marco Pelliccia, 2012. "Risk-sharing and probabilistic network structure," Birkbeck Working Papers in Economics and Finance 1214, Birkbeck, Department of Economics, Mathematics & Statistics.
    7. Iori Giulia & Kapar Burcu & Olmo Jose, 2015. "Bank characteristics and the interbank money market: a distributional approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(3), pages 249-283, June.
    8. Kok, Christoffer & Gross, Marco, 2013. "Measuring contagion potential among sovereigns and banks using a mixed-cross-section GVAR," Working Paper Series 1570, European Central Bank.
    9. Peltonen, Tuomas A. & Scheicher, Martin & Vuillemey, Guillaume, 2014. "The network structure of the CDS market and its determinants," Journal of Financial Stability, Elsevier, vol. 13(C), pages 118-133.
    10. Fabio Saracco & Riccardo Di Clemente & Andrea Gabrielli & Tiziano Squartini, 2015. "Detecting early signs of the 2007-2008 crisis in the world trade," Papers 1508.03533, arXiv.org, revised Jul 2016.
    11. Gabrieli, S., 2012. "Too-connected versus too-big-to-fail: banks’ network centrality and overnight interest rates," Working papers 398, Banque de France.

    More about this item

    Keywords

    Network analysis; Network centrality indicators; Money market; Financial crisis;

    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • G01 - Financial Economics - - General - - - Financial Crises
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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