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On the Distribution of Links in the Interbank Network: Evidence from the e-Mid Overnight Money Market

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  • Daniel Fricke
  • Thomas Lux

Abstract

Previous literature on statistical properties of interbank loans has reported various power-laws, particularly for the degree distribution (i.e. the distribution of credit links between institutions). In this paper, we revisit data for the Italian interbank network based on overnight loans recorded on the e-MID trading platform during the period 1999-2010 using both daily and quarterly aggregates. In con- trast to previous authors, we find no evidence in favor of scale-free networks. Rather, the data are best described by negative Binomial distributions. For quarterly data, Weibull, Gamma, and Exponential distributions tend to provide comparable ts. We find comparable re- sults when investigating the distribution of the number of transactions, even though in this case the tails of the quarterly variables are much fatter. The absence of power-law behavior casts doubts on the claim that interbank data fall into the category of scale-free networks

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Bibliographic Info

Paper provided by Kiel Institute for the World Economy in its series Kiel Working Papers with number 1819.

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Length: 41 pages
Date of creation: Jan 2013
Date of revision:
Handle: RePEc:kie:kieliw:1819

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Keywords: interbank market; network models;

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References

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  1. Giorgio Fagiolo & Mauro Napoletano & Andrea Roventini, 2008. "Are output growth-rate distributions fat-tailed? some evidence from OECD countries," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(5), pages 639-669.
  2. 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.
  3. Nier, Erlend & Yang, Jing & Yorulmazer, Tanju & Alentorn, Amadeo, 2008. "Network models and financial stability," Bank of England working papers 346, Bank of England.
  4. M. Goldstein & S. Morris & G. Yen, 2004. "Problems with fitting to the power-law distribution," The European Physical Journal B - Condensed Matter and Complex Systems, Springer, vol. 41(2), pages 255-258, 09.
  5. Benoit Mandelbrot, 1963. "The Variation of Certain Speculative Prices," The Journal of Business, University of Chicago Press, vol. 36, pages 394.
  6. 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.
  7. Thomas Lux, Daniel Fricke, 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.
  8. Xavier Gabaix, 1999. "Zipf'S Law For Cities: An Explanation," The Quarterly Journal of Economics, MIT Press, vol. 114(3), pages 739-767, August.
  9. Karl Finger & Daniel Fricke & Thomas Lux, 2012. "Network Analysis of the e-MID Overnight Money Market: The Informational Value of Different Aggregation Levels for Intrinsic Dynamic Processes," Kiel Working Papers 1782, Kiel Institute for the World Economy.
  10. Beaupain, Renaud & Durré, Alain, 2012. "Nonlinear liquidity adjustments in the euro area overnight money market," Working Paper Series 1500, European Central Bank.
  11. Xavier Gabaix & Rustam Ibragimov, 2007. "Rank-1/2: A Simple Way to Improve the OLS Estimation of Tail Exponents," NBER Technical Working Papers 0342, National Bureau of Economic Research, Inc.
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Cited by:
  1. Karl Finger & Daniel Fricke & Thomas Lux, 2012. "Network Analysis of the e-MID Overnight Money Market: The Informational Value of Different Aggregation Levels for Intrinsic Dynamic Processes," Kiel Working Papers 1782, Kiel Institute for the World Economy.

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