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Testing the bivariate distribution of daily equity returns using copulas. An application to the Spanish stock market

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  • Oriol Roch Casellas
  • Antonio Alegre Escolano

    (Universitat de Barcelona)

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    Abstract

    In this paper we deal with the identification of dependencies between time series of equity returns. Marginal distribution functions are assumed to be known, and a bivariate chi-square test of fit is applied in a fully parametric copula approach. Several families of copulas are fitted and compared with Spanish stock market data. The results show that the t-copula generally outperforms other dependence structures, and highlight the difficulty in adjusting a significant number of bivariate data series.

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    Bibliographic Info

    Paper provided by Universitat de Barcelona. Espai de Recerca en Economia in its series Working Papers in Economics with number 143.

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    Length: 18 pages
    Date of creation: 2005
    Date of revision:
    Handle: RePEc:bar:bedcje:2005143

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    Postal: Espai de Recerca en Economia, Facultat de Ciències Econòmiques. Tinent Coronel Valenzuela, Num 1-11 08034 Barcelona. Spain.
    Web page: http://www.ere.ub.es
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    1. François Longin, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, American Finance Association, vol. 56(2), pages 649-676, 04.
    2. U. Cherubini & E. Luciano, 2002. "Bivariate option pricing with copulas," Applied Mathematical Finance, Taylor & Francis Journals, Taylor & Francis Journals, vol. 9(2), pages 69-85.
    3. W. Breymann & A. Dias & P. Embrechts, 2003. "Dependence structures for multivariate high-frequency data in finance," Quantitative Finance, Taylor & Francis Journals, Taylor & Francis Journals, vol. 3(1), pages 1-14.
    4. Andrew Patton, 2004. "Modelling Asymmetric Exchange Rate Dependence," Working Papers, Warwick Business School, Finance Group wp04-04, Warwick Business School, Finance Group.
    5. Yanqin Fan & Xiaohong Chen & Andrew Patton, 2004. "(IAM Series No 003) Simple Tests for Models of Dependence Between Multiple Financial Time Series, with Applications to U.S. Equity Returns and Exchange Rates," FMG Discussion Papers, Financial Markets Group dp483, Financial Markets Group.
    6. Christian Genest & Jean-François Quessy & Bruno Rémillard, 2006. "Goodness-of-fit Procedures for Copula Models Based on the Probability Integral Transformation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(2), pages 337-366.
    7. Andrew J. Patton, 2004. "On the Out-of-Sample Importance of Skewness and Asymmetric Dependence for Asset Allocation," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(1), pages 130-168.
    8. Klugman, Stuart A. & Parsa, Rahul, 1999. "Fitting bivariate loss distributions with copulas," Insurance: Mathematics and Economics, Elsevier, vol. 24(1-2), pages 139-148, March.
    9. Fernández, C. & Steel, M.F.J., 1996. "On Bayesian Modelling of Fat Tails and Skewness," Discussion Paper, Tilburg University, Center for Economic Research 1996-58, Tilburg University, Center for Economic Research.
    10. Linden, Mikael, 2001. "A Model for Stock Return Distribution," International Journal of Finance & Economics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 6(2), pages 159-69, April.
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