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Archimedean copulae for risk measurement

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  • Giovanni De Luca
  • Giorgia Rivieccio

Abstract

In this paper some Archimedean copula functions for bivariate financial returns are studied. The choice of this family is due to their ability to capture the tail dependence, which is an association measure we can detect in many bivariate financial time-series. A time-varying version of these copulae is also investigated. Finally, the Value-at-Risk is computed and its performance is compared across different copula specifications.

Suggested Citation

  • Giovanni De Luca & Giorgia Rivieccio, 2009. "Archimedean copulae for risk measurement," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(8), pages 907-924.
    • Handle: RePEc:taf:japsta:v:36:y:2009:i:8:p:907-924
    DOI: 10.1080/02664760802520785
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    References listed on IDEAS

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    1. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
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    4. Giacomini, Enzo & Härdle, Wolfgang Karl, 2005. "Value-at-risk calculations with time varying copulae," SFB 649 Discussion Papers 2005-004, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    6. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
    7. repec:hum:wpaper:sfb649dp2005-004 is not listed on IDEAS
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    Cited by:

    1. Fabian Capitanio & Giorgia Rivieccio & Felice Adinolfi, 2020. "Food Price Volatility and Asymmetries in Rural Areas of South Mediterranean Countries: A Copula-Based GARCH Model," IJERPH, MDPI, vol. 17(16), pages 1-14, August.
    2. Rebecca M. Baker & Tahani Coolen-Maturi & Frank P. A. Coolen, 2017. "Nonparametric predictive inference for stock returns," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(8), pages 1333-1349, June.
    3. F. Louzada & P. H. Ferreira, 2016. "Modified inference function for margins for the bivariate clayton copula-based SUN Tobit Model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(16), pages 2956-2976, December.
    4. Frederik Michiels & Ann De Schepper, 2012. "How to improve the fit of Archimedean copulas by means of transforms," Statistical Papers, Springer, vol. 53(2), pages 345-355, May.

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