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Joint characteristic functions construction via copulas

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  • Komelj, Janez
  • Perman, Mihael
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    Abstract

    When modelling dependent risks it is important to be able to generate joint distributions with given marginals. One of the ways which may be useful in connection with using the Fast Fourier Transform is to construct joint characteristic functions from marginal characteristic functions. In this paper a class of n-dimensional continuous copulas is presented which in turn lead to a simple construction of joint characteristic functions with given marginal characteristic functions. Bounds on various measures of correlation are also given.

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    Bibliographic Info

    Article provided by Elsevier in its journal Insurance: Mathematics and Economics.

    Volume (Year): 47 (2010)
    Issue (Month): 2 (October)
    Pages: 137-143

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    Handle: RePEc:eee:insuma:v:47:y:2010:i:2:p:137-143

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    Web page: http://www.elsevier.com/locate/inca/505554

    Related research

    Keywords: IM10 Copulas Distortion functions Joint distributions with given marginals Characteristic functions;

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    1. I. Bairamov & S. Kotz & M. Bekci, 2001. "New generalized Farlie-Gumbel-Morgenstern distributions and concomitants of order statistics," Journal of Applied Statistics, Taylor & Francis Journals, Taylor & Francis Journals, vol. 28(5), pages 521-536.
    2. Cécile Amblard & Stéphane Girard, 2009. "A new extension of bivariate FGM copulas," Metrika, Springer, Springer, vol. 70(1), pages 1-17, June.
    3. repec:sae:ecolab:v:16:y:2006:i:2:p:1-2 is not listed on IDEAS
    4. Lynn Wirch, Julia & Hardy, Mary R., 1999. "A synthesis of risk measures for capital adequacy," Insurance: Mathematics and Economics, Elsevier, vol. 25(3), pages 337-347, December.
    5. Rodríguez-Lallena, José Antonio & Úbeda-Flores, Manuel, 2004. "A new class of bivariate copulas," Statistics & Probability Letters, Elsevier, Elsevier, vol. 66(3), pages 315-325, February.
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