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How Does The Eurodollar Interest Rate Behave?

Author

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  • TIZIANA DI MATTEO

    (INFM-Dipartimento di Fisica, Università degli Studi di Salerno, 84081 Baronissi (Salerno), Italy)

  • TOMASO ASTE

    (INFM-Dipartimento di Fisica, Università di Genova, via Dodecaneso 33, 16146 Genova, Italy;
    AAS, Sal. Spianata Castelletto 16, 16124 Genova, Italy)

Abstract

An empirical analysis on Eurodollar interest rates daily data in the time period 1990–1996, is performed and compared with Libor data in the time period 1984–1998. The complementary cumulative distributions for the daily fluctuations at different maturity dates and the Power Spectral Density are computed. We find that the probability distribution shows "fat" tails with non-Gaussian behaviours. Moreover, we study the correlations among Eurodollar interest rates fluctuations with different maturity dates. By using an original clustering linkage, we show how the collective motion of the interest rates curve can be analyzed in sub-groups of maturity dates with similar behaviours.

Suggested Citation

  • Tiziana Di Matteo & Tomaso Aste, 2002. "How Does The Eurodollar Interest Rate Behave?," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 5(01), pages 107-122.
    • Handle: RePEc:wsi:ijtafx:v:05:y:2002:i:01:n:s021902490200133x
    DOI: 10.1142/S021902490200133X
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    2. Cajueiro, Daniel O. & Tabak, Benjamin M., 2007. "Long-range dependence and multifractality in the term structure of LIBOR interest rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 603-614.
    3. Tabak, Benjamin M. & Serra, Thiago R. & Cajueiro, Daniel O., 2009. "The expectation hypothesis of interest rates and network theory: The case of Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(7), pages 1137-1149.
    4. Ausloos, M. & Lambiotte, R., 2007. "Clusters or networks of economies? A macroeconomy study through Gross Domestic Product," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 16-21.
    5. Nicoló Musmeci & Tomaso Aste & T Di Matteo, 2015. "Relation between Financial Market Structure and the Real Economy: Comparison between Clustering Methods," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-24, March.
    6. Alderweireld, Thomas & Nuyts, Jean, 2004. "Detailed empirical study of the term structure of interest rates. Emergence of power laws and scaling laws," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 331(3), pages 602-616.
    7. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    8. Thomas Alderweireld & Jean Nuyts, 2003. "Term Structure of Interest Rates. Emergence of Power Laws and Scaling Laws," EERI Research Paper Series EERI_RP_2003_05, Economics and Econometrics Research Institute (EERI), Brussels.
    9. Thomas Alderweireld & Jean Nuyts, 2003. "Term Structure of Interest Rates.Emergence of Power Laws and Scaling Laws," Econometrics 0306001, University Library of Munich, Germany.
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