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Test of the Gaussian Copula on the Swedish Stock Market

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  • Söderberg, Jonas

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    (Centre for Labour Market Policy Research (CAFO))

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    Abstract

    This paper examines whether the pairwise comovement between stocks quoted on the Stockholm stock exchange can be correctly quantified by the Gaussian copula, i.e., by linear correlation. Two different methods are used to test whether the dependence on the Swedish stock market can be modeled by the Gaussian copula. From these tests, we come to the conclusion that the Gaussian copula is not an appropriate choice of copula for the Swedish stock market. We also come to the same conclusion when observing sector and industry indices on the Swedish stock market. However, if performing a GARCH filtering of the return series, there is a substantial decrease in the number of pairs of either stocks or indices for which the Gaussian copula can be rejected. For the two test methods, a notable difference in the rejection rate of the Gaussian copula can also be observed.

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    Bibliographic Info

    Paper provided by Centre for Labour Market Policy Research (CAFO), School of Business and Economics, Linnaeus University in its series CAFO Working Papers with number 2009:9.

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    Length: 24 pages
    Date of creation: 01 Dec 2008
    Date of revision:
    Handle: RePEc:hhs:vxcafo:2009_009

    Contact details of provider:
    Postal: Centre for Labour Market Policy Research (CAFO), School of Business and Economics, Linnaeus University, SE 351 95 Växjö, Sweden
    Phone: +46 470 70 87 64
    Web page: http://lnu.se/research-groups/cafo?l=en
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    Related research

    Keywords: Risk management; Gaussian copula; Swedish stock markets; GARCH filtering;

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    1. Brännäs, Kurt & Quoreshi, Shahiduzzaman & Simonsen, Ola, 2002. "Extreme-Value Characteristics in Daily Time Series of Swedish Stock Returns," UmeÃ¥ Economic Studies 597, Umeå University, Department of Economics.
    2. François Longin, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, 04.
    3. Ser-Huang Poon, 2004. "Extreme Value Dependence in Financial Markets: Diagnostics, Models, and Financial Implications," Review of Financial Studies, Society for Financial Studies, vol. 17(2), pages 581-610.
    4. Robert Engle, 2001. "GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 157-168, Fall.
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