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Tracking the Libor rate

Author

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  • Rosa Abrantes-Metz
  • Sofia Villas-Boas
  • George Judge

Abstract

With an eye to providing a methodology for tracking the dynamic integrity of prices for important market indicators, in this article we use Benford second digit (SD) reference distribution to track the daily London Interbank Offered Rate (Libor) over the period 2005 to 2008. This reference, known as Benford's law, is present in many naturally occurring numerical data sets as well as in several financial data sets. We find that in two recent periods, Libor rates depart significantly from the expected Benford reference distribution. This raises potential concerns relative to the unbiased nature of the signals coming from the 16 banks from which the Libor is computed and the usefulness of the Libor as a major economic indicator.

Suggested Citation

  • Rosa Abrantes-Metz & Sofia Villas-Boas & George Judge, 2011. "Tracking the Libor rate," Applied Economics Letters, Taylor & Francis Journals, vol. 18(10), pages 893-899.
  • Handle: RePEc:taf:apeclt:v:18:y:2011:i:10:p:893-899
    DOI: 10.1080/13504851.2010.515197
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    References listed on IDEAS

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    1. Tam Cho, Wendy K. & Gaines, Brian J., 2007. "Breaking the (Benford) Law: Statistical Fraud Detection in Campaign Finance," The American Statistician, American Statistical Association, vol. 61, pages 218-223, August.
    2. David Giles, 2007. "Benford's law and naturally occurring prices in certain ebaY auctions," Applied Economics Letters, Taylor & Francis Journals, vol. 14(3), pages 157-161.
    3. George Judge & Laura Schechter, 2009. "Detecting Problems in Survey Data Using Benford’s Law," Journal of Human Resources, University of Wisconsin Press, vol. 44(1).
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    Citations

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    Cited by:

    1. Marcel Ausloos & Rosella Castellano & Roy Cerqueti, 2016. "Regularities and Discrepancies of Credit Default Swaps: a Data Science approach through Benford's Law," Papers 1603.01103, arXiv.org.
    2. Donna, Javier & Espin-Sanchez, Jose, 2014. "Complements and Substitutes in Sequential Auctions: The Case of Water Auctions," MPRA Paper 55079, University Library of Munich, Germany.
    3. Marcel Ausloos & Roy Cerqueti & Tariq A. Mir, 2017. "Data science for assessing possible tax income manipulation: The case of Italy," Papers 1709.02129, arXiv.org.
    4. Monticini, Andrea & Thornton, Daniel L., 2013. "The effect of underreporting on LIBOR rates," Journal of Macroeconomics, Elsevier, vol. 37(C), pages 345-348.
    5. Diehl, Christoph, 2014. "The LIBOR mechanism and Related Games," Center for Mathematical Economics Working Papers 482, Center for Mathematical Economics, Bielefeld University.
    6. Tariq Ahmad Mir & Marcel Ausloos & Roy Cerqueti, 2014. "Benford's law predicted digit distribution of aggregated income taxes: the surprising conformity of Italian cities and regions," Papers 1410.2890, arXiv.org.
    7. Smales, Lee A., 2016. "News sentiment and bank credit risk," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 37-61.
    8. Carrera, César, 2015. "Tracking exchange rate management in Latin America," Review of Financial Economics, Elsevier, vol. 25(C), pages 35-41.
    9. Abrantes-Metz, Rosa M. & Kraten, Michael & Metz, Albert D. & Seow, Gim S., 2012. "Libor manipulation?," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 136-150.
    10. Carrera, César, 2014. "Tracking the Exchange Rate Management in Latin America," Working Papers 2014-020, Banco Central de Reserva del Perú.
    11. Bariviera, Aurelio F. & Martín, María T. & Plastino, Angelo & Vampa, Victoria, 2016. "LIBOR troubles: Anomalous movements detection based on maximum entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 401-407.
    12. Aneta Hryckiewicz & Piotr Mielus & Karolina Skorulska & Malgorzata Snarska, 2018. "Does a bank levy increase frictions on the interbank market?," Working Papers 2018-033, Warsaw School of Economics, Collegium of Economic Analysis.
    13. Aurelio Fernandez Bariviera & María Belén Guercio & Lisana B. Martinez & Osvaldo A. Rosso, 2015. "The (in)visible hand in the Libor market: an information theory approach," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 88(8), pages 1-9, August.
    14. Thomas Stoerk, 2015. "Statistical corruption in Beijing’s air quality data has likely ended in 2012," GRI Working Papers 194, Grantham Research Institute on Climate Change and the Environment.
    15. Aurelio Fernandez Bariviera & M. Bel'en Guercio & Lisana B. Martinez, 2015. "Data manipulation detection via permutation information theory quantifiers," Papers 1501.04123, arXiv.org.
    16. Samà, Danilo, 2014. "Cartel Detection and Collusion Screening: An Empirical Analysis of the London Metal Exchange," MPRA Paper 55363, University Library of Munich, Germany.
    17. Brooks, Robert & Cline, Brandon N. & Enders, Walter, 2015. "A comparison of the information in the LIBOR and CMT term structures of interest rates," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 239-253.
    18. Nicole El Karoui & Stéphane Loisel & Jean-Luc Prigent & Julien Vedani, 2015. "Market inconsistencies of the market-consistent European life insurance economic valuations: pitfalls and practical solutions," Working Papers hal-01242023, HAL.
    19. Aurelio F. Bariviera & M. Belen Guercio & Lisana B. Martinez & Osvaldo A. Rosso, 2015. "A permutation Information Theory tour through different interest rate maturities: the Libor case," Papers 1509.00217, arXiv.org.

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