Goodness-of-fit tests for copulas: A review and a power study
AbstractMany proposals have been made recently for goodness-of-fit testing of copula models. After reviewing them briefly, the authors concentrate on "blanket tests", i.e.,Â those whose implementation requires neither an arbitrary categorization of the data nor any strategic choice of smoothing parameter, weight function, kernel, window, etc. The authors present a critical review of these procedures and suggest new ones. They describe and interpret the results of a large Monte Carlo experiment designed to assess the effect of the sample size and the strength of dependence on the level and power of the blanket tests for various combinations of copula models under the null hypothesis and the alternative. To circumvent problems in the determination of the limiting distribution of the test statistics under composite null hypotheses, they recommend the use of a double parametric bootstrap procedure, whose implementation is detailed. They conclude with a number of practical recommendations.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Insurance: Mathematics and Economics.
Volume (Year): 44 (2009)
Issue (Month): 2 (April)
Contact details of provider:
Web page: http://www.elsevier.com/locate/inca/505554
Anderson-Darling statistic Copula Cramér-von Mises statistic Gaussian process Goodness-of-fit Kendall's tau Kolmogorov-Smirnov statistic Monte Carlo simulation Parametric bootstrap Power study Pseudo-observations P-values;
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Scaillet, Olivier, 2007.
"Kernel-based goodness-of-fit tests for copulas with fixed smoothing parameters,"
Journal of Multivariate Analysis, Elsevier,
Elsevier, vol. 98(3), pages 533-543, March.
- Olivier Scaillet, 2005. "Kernel Based Goodness-of-Fit Tests for Copulas with Fixed Smoothing Parameters," FAME Research Paper Series, International Center for Financial Asset Management and Engineering rp145, International Center for Financial Asset Management and Engineering.
- Tomasz Burzykowski & Geert Molenberghs & Marc Buyse, 2004. "The validation of surrogate end points by using data from randomized clinical trials: a case-study in advanced colorectal cancer," Journal of the Royal Statistical Society Series A, Royal Statistical Society, Royal Statistical Society, vol. 167(1), pages 103-124.
- Yannick Malevergne & Didier Sornette, 2003.
"Testing the Gaussian copula hypothesis for financial assets dependences,"
- Y. Malevergne & D. Sornette, 2003. "Testing the Gaussian copula hypothesis for financial assets dependences," Quantitative Finance, Taylor & Francis Journals, Taylor & Francis Journals, vol. 3(4), pages 231-250.
- Y. Malevergne & D. Sornette, 2001. "Testing the Gaussian Copula Hypothesis for Financial Assets Dependences," Finance, EconWPA 0111003, EconWPA.
- Y. Malevergne & D. Sornette, 2001. "Testing the Gaussian Copula Hypothesis for Financial Assets Dependences," Papers, arXiv.org cond-mat/0111310, arXiv.org.
- Thierry Ane & Cecile Kharoubi, 2003. "Dependence Structure and Risk Measure," The Journal of Business, University of Chicago Press, University of Chicago Press, vol. 76(3), pages 411-438, July.
- Markus Junker & Angelika May, 2005. "Measurement of aggregate risk with copulas," Econometrics Journal, Royal Economic Society, Royal Economic Society, vol. 8(3), pages 428-454, December.
- repec:sae:ecolab:v:16:y:2006:i:2:p:1-2 is not listed on IDEAS
- Fang, Hong-Bin & Fang, Kai-Tai & Kotz, Samuel, 2002. "The Meta-elliptical Distributions with Given Marginals," Journal of Multivariate Analysis, Elsevier, Elsevier, vol. 82(1), pages 1-16, July.
- Xiaohong Chen & Yanqin Fan & Victor Tsyrennifov, 2004.
"Efficient Estimation of Semiparametric Multivariate Copula Models,"
Vanderbilt University Department of Economics Working Papers, Vanderbilt University Department of Economics
0420, Vanderbilt University Department of Economics.
- Chen, Xiaohong & Fan, Yanqin & Tsyrennikov, Viktor, 2006. "Efficient Estimation of Semiparametric Multivariate Copula Models," Journal of the American Statistical Association, American Statistical Association, American Statistical Association, vol. 101, pages 1228-1240, September.
- 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.
- Klugman, Stuart A. & Parsa, Rahul, 1999. "Fitting bivariate loss distributions with copulas," Insurance: Mathematics and Economics, Elsevier, Elsevier, vol. 24(1-2), pages 139-148, March.
- Joe, Harry, 2005. "Asymptotic efficiency of the two-stage estimation method for copula-based models," Journal of Multivariate Analysis, Elsevier, Elsevier, vol. 94(2), pages 401-419, June.
- Kim, Gunky & Silvapulle, Mervyn J. & Silvapulle, Paramsothy, 2007. "Comparison of semiparametric and parametric methods for estimating copulas," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 51(6), pages 2836-2850, March.
- Panchenko, Valentyn, 2005. "Goodness-of-fit test for copulas," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 355(1), pages 176-182.
- Fermanian, Jean-David, 2005. "Goodness-of-fit tests for copulas," Journal of Multivariate Analysis, Elsevier, Elsevier, vol. 95(1), pages 119-152, July.
- Frahm, Gabriel & Junker, Markus & Szimayer, Alexander, 2003. "Elliptical copulas: applicability and limitations," Statistics & Probability Letters, Elsevier, Elsevier, vol. 63(3), pages 275-286, July.
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page. reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.