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Detecting And Modeling Tail Dependence

Author

Listed:
  • FABIO BELLINI

    (Dipartimento di Metodi Quantitativi per le Scienze Economiche ed Aziendali, University of Milan-Bicocca, Piazza Ateneo Nuovo, 1 Milan, 20126, Italy)

  • GIANNA FIGÀ-TALAMANCA

    (Dipartimento di Organizzazione Aziendale ed Amministrazione Pubblica, University of Calabria, Ponte Bucci, Cubo 3B, Arcavacata di Rende, 87036, Italy)

Abstract

The aim of this work is to develop a nonparametric tool for detecting dependence in the tails of financial data. We provide a simple method to locate and measure serial dependence in the tails, based on runs tests. Our empirical investigations on many financial time series reveal a strong departure from independence for daily logreturns, which is not filtered out by usual Garch models.

Suggested Citation

  • Fabio Bellini & Gianna Figà-Talamanca, 2004. "Detecting And Modeling Tail Dependence," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 7(03), pages 269-287.
    • Handle: RePEc:wsi:ijtafx:v:07:y:2004:i:03:n:s0219024904002426
    DOI: 10.1142/S0219024904002426
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    References listed on IDEAS

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    1. Jon Danielsson & Casper G. De Vries, 2000. "Value-at-Risk and Extreme Returns," Annals of Economics and Statistics, GENES, issue 60, pages 239-270.
    2. repec:adr:anecst:y:2000:i:60:p:10 is not listed on IDEAS
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