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A fitness model for the Italian Interbank Money Market


  • G. De Masi

    (Dipartimento di Fisica, Universita' dell'Aquila Coppito
    INFM-CNR Centro SMC and Dipartimento di Fisica Universit\'a di Roma "La Sapienza" Roma, Italy)

  • G. Iori

    (Department of Economics, City University, London, UK)

  • G. Caldarelli

    (INFM-CNR Centro SMC and Dipartimento di Fisica Universit\'a di Roma "La Sapienza" Roma, Italy
    Centro Studi e Museo della Fisica Enrico Fermi, Roma, Italy)


We use the theory of complex networks in order to quantitatively characterize the formation of communities in a particular financial market. The system is composed by different banks exchanging on a daily basis loans and debts of liquidity. Through topological analysis and by means of a model of network growth we can determine the formation of different group of banks characterized by different business strategy. The model based on Pareto's Law makes no use of growth or preferential attachment and it reproduces correctly all the various statistical properties of the system. We believe that this network modeling of the market could be an efficient way to evaluate the impact of different policies in the market of liquidity.

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  • G. De Masi & G. Iori & G. Caldarelli, 2006. "A fitness model for the Italian Interbank Money Market," Papers physics/0610108,
  • Handle: RePEc:arx:papers:physics/0610108

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    1. Lo, Andrew W. & Craig MacKinlay, A., 1990. "An econometric analysis of nonsynchronous trading," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 181-211.
    2. Damien Challet & Tobias Galla, 2005. "Price return autocorrelation and predictability in agent-based models of financial markets," Quantitative Finance, Taylor & Francis Journals, vol. 5(6), pages 569-576.
    3. David M. Cutler & James M. Poterba & Lawrence H. Summers, 1991. "Speculative Dynamics," Review of Economic Studies, Oxford University Press, vol. 58(3), pages 529-546.
    4. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    5. LeBaron, Blake, 1992. "Some Relations between Volatility and Serial Correlations in Stock Market Returns," The Journal of Business, University of Chicago Press, vol. 65(2), pages 199-219, April.
    6. Sentana, Enrique & Wadhwani, Sushil B, 1992. "Feedback Traders and Stock Return Autocorrelations: Evidence from a Century of Daily Data," Economic Journal, Royal Economic Society, vol. 102(411), pages 415-425, March.
    7. Safvenblad, Patrik, 2000. "Trading volume and autocorrelation: Empirical evidence from the Stockholm Stock Exchange," Journal of Banking & Finance, Elsevier, vol. 24(8), pages 1275-1287, August.
    8. Asger Lunde & Peter R. Hansen, 2005. "A forecast comparison of volatility models: does anything beat a GARCH(1,1)?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
    9. Kaul, Aditya & Sapp, Stephen, 2005. "Trading Activity and Foreign Exchange Market Quality," CEI Working Paper Series 2005-9, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
    10. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    11. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    12. John M. Maheu & Thomas H. McCurdy, 2002. "Nonlinear Features of Realized FX Volatility," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 668-681, November.
    13. Simone Bianco & Roberto Renò, 2006. "Dynamics of intraday serial correlation in the Italian futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 26(1), pages 61-84, January.
    14. Fulvio Corsi & Gilles Zumbach & Ulrich A. Muller & Michel M. Dacorogna, 2001. "Consistent High-precision Volatility from High-frequency Data," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 30(2), pages 183-204, July.
    15. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
    16. Jessica James, 2003. "Robustness of simple trend-following strategies," Quantitative Finance, Taylor & Francis Journals, vol. 3(6), pages 114-116.
    17. Lo, Andrew W. & MacKinlay, A. Craig, 1989. "The size and power of the variance ratio test in finite samples : A Monte Carlo investigation," Journal of Econometrics, Elsevier, vol. 40(2), pages 203-238, February.
    18. Deo, Rohit S. & Richardson, Matthew, 2003. "On The Asymptotic Power Of The Variance Ratio Test," Econometric Theory, Cambridge University Press, vol. 19(02), pages 231-239, April.
    19. Faust, Jon, 1992. "When Are Variance Ratio Tests for Serial Dependence Optimal?," Econometrica, Econometric Society, vol. 60(5), pages 1215-1226, September.
    20. Cecchetti, Stephen G & Lam, Pok-sang, 1994. "Variance-Ratio Tests: Small-Sample Properties with an Application to International Output Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 177-186, April.
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