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Chapter 4 Copula Theory Applied to Hedge Funds Dependence Structure Determination

Author

Listed:
  • Rania Hentati

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Jean-Luc Prigent

    (THEMA - Théorie économique, modélisation et applications - UCP - Université de Cergy Pontoise - Université Paris-Seine - CNRS - Centre National de la Recherche Scientifique)

Abstract

Purpose - In this chapter, copula theory is used to model dependence structure between hedge fund returns series. Methodology/approach - Goodness-of-fit tests, based on the Kendall's functions, are applied as selection criteria of the "best" copula. After estimating the parametric copula that best fits the used data, we apply previous results to construct the cumulative distribution functions of the equally weighted portfolios. Findings - The empirical validation shows that copula clearly allows better estimation of portfolio returns including hedge funds. The three studied portfolios reject the assumption of multivariate normality of returns. The chosen structure is often of Student type when only indices are considered. In the case of portfolios composed by only hedge funds, the dependence structure is of Franck type. Originality/value of the chapter - Introducing goodness-of-fit bootstrap method to validate the choice of the best structure of dependence is relevant for hedge fund portfolios. Copulas would be introduced to provide better estimations of performance measures.

Suggested Citation

  • Rania Hentati & Jean-Luc Prigent, 2010. "Chapter 4 Copula Theory Applied to Hedge Funds Dependence Structure Determination," Post-Print hal-00607102, HAL.
    • Handle: RePEc:hal:journl:hal-00607102
    DOI: 10.1108/S1571-0386(2010)0000020009
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    Cited by:

    1. Hasan, Kazi Nazmul & Preece, Robin & Milanović, Jovica V., 2019. "Existing approaches and trends in uncertainty modelling and probabilistic stability analysis of power systems with renewable generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 168-180.

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