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Copula Models of the Joint Distribution of Exchange Rates

Author

Listed:
  • Antonov I. N.

    (Astrakhan State University)

  • Knyazev A. G.
  • Lepekhin O. A.

Abstract

The paper aims at investigating the joint distribution of currency rates using HAC, HKC and Vine copulas in several time periods. Models were constructed using Archimedean copulas including Gumbel-Hougaard, Joe BB1 and Frank copulas, and their parameters were estimated by maximum likelihood. The best models were built using hierarchical Archimedean copulas and the worst were obtained with vine copulas. In comparison with the HAC, the main advantage of hierarchical Kendall copulas is the possibility to use a two-parameter copula Joe BB1. The best models were obtained with Frank copula, while Gumbel-Hougaard copula has shown a decent result only in the third period. Additionally, in this paper was made an attempt to get the forecast of exchange rates using Kendall’s and Marshall-Olkin’s algorithms. The most accurate forecast was obtained with Gumbel-Hougaard copula for euro and franc.

Suggested Citation

  • Antonov I. N. & Knyazev A. G. & Lepekhin O. A., 2016. "Copula Models of the Joint Distribution of Exchange Rates," World of economics and management / Vestnik NSU. Series: Social and Economics Sciences, Socionet, vol. 16(4), pages 20-38.
    • Handle: RePEc:nos:wjflnh:2016_4_02e
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    References listed on IDEAS

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    1. Okhrin, Ostap & Ristig, Alexander, 2014. "Hierarchical Archimedean Copulae: The HAC Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 58(i04).
    2. Hofert, Marius, 2011. "Efficiently sampling nested Archimedean copulas," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 57-70, January.
    3. Barbe, Philippe & Genest, Christian & Ghoudi, Kilani & Rémillard, Bruno, 1996. "On Kendall's Process," Journal of Multivariate Analysis, Elsevier, vol. 58(2), pages 197-229, August.
    4. Penikas, Henry, 2014. "Investment portfolio risk modelling based on hierarchical copulas," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 35(3), pages 18-38.
    5. Puzanova, Natalia, 2011. "A hierarchical Archimedean copula for portfolio credit risk modelling," Discussion Paper Series 2: Banking and Financial Studies 2011,14, Deutsche Bundesbank.
    6. Dominique Guegan & Pierre-André Maugis, 2010. "An Econometric Study of Vine Copulas," Documents de travail du Centre d'Economie de la Sorbonne 10040, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    7. Christian Genest & Johanna Nešlehová & Johanna Ziegel, 2011. "Rejoinder on: Inference in multivariate Archimedean copula models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(2), pages 290-292, August.
    8. Fotios C. Harmantzis & Linyan Miao & Yifan Chien, 2006. "Empirical study of value-at-risk and expected shortfall models with heavy tails," Journal of Risk Finance, Emerald Group Publishing, vol. 7(2), pages 117-135, March.
    9. Brechmann, Eike Christian & Schepsmeier, Ulf, 2013. "Modeling Dependence with C- and D-Vine Copulas: The R Package CDVine," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 52(i03).
    10. Dominique Guegan & Pierre-André Maugis, 2010. "An Econometric Study of Vine Copulas," Post-Print halshs-00492124, HAL.
    11. Penikas, H., 2010. "Financial Applications of Copula-Models," Journal of the New Economic Association, New Economic Association, issue 7, pages 24-44.
    12. Christian Genest & Johanna Nešlehová & Johanna Ziegel, 2011. "Inference in multivariate Archimedean copula models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(2), pages 223-256, August.
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    More about this item

    Keywords

    Archimedean copulas; currency; forecast; Frank copula; Gumbel-Hougaard copula; HAC; HKC; Joe BB1 copula; Marshall-Olkin’s algorithm; sampling via Kendall’s Distribution; Vine.;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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