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Detection of Structural Breaks in Copula Models

  • Brodsky, Boris

    ()

    (Central Economic-Mathematical Institute, Russia)

  • Penikas, Henry

    ()

    (Higher School of Economics, Russia)

  • Safaryan, Irina

    ()

    (Russian-Armenian (Slavonic) State University)

Registered author(s):

    The paper presents the research results on detection of structural breaks in copula models of multivariate time-series. A nonparametric method of structural break identification and estimation is used and its asymptotic characteristics (probabilities of the I and II-type errors, probability of estimation error) are analyzed. Simulation test results applied to Clayton and Gumbel copulas are presented and discussed

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    File URL: http://pe.cemi.rssi.ru/pe_2009_4_03-15.pdf
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    Article provided by Publishing House "SINERGIA PRESS" in its journal Applied Econometrics.

    Volume (Year): 16 (2009)
    Issue (Month): 4 ()
    Pages: 3-15

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    Handle: RePEc:ris:apltrx:0038
    Contact details of provider: Web page: http://appliedeconometrics.cemi.rssi.ru/

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    1. Y. Malevergne & D. Sornette, 2001. "Testing the Gaussian Copula Hypothesis for Financial Assets Dependences," Papers cond-mat/0111310, arXiv.org.
    2. Penikas, Henry & Simakova, Varvara, 2009. "Interest Rate Risk Management Based on Copula-GARCH Models," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 13(1), pages 3-36.
    3. Markus Junker & Angelika May, 2005. "Measurement of aggregate risk with copulas," Econometrics Journal, Royal Economic Society, vol. 8(3), pages 428-454, December.
    4. Rémillard, Bruno & Scaillet, Olivier, 2009. "Testing for equality between two copulas," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 377-386, March.
    5. Genest, Christian & Rémillard, Bruno & Beaudoin, David, 2009. "Goodness-of-fit tests for copulas: A review and a power study," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 199-213, April.
    6. W. Breymann & A. Dias & P. Embrechts, 2003. "Dependence structures for multivariate high-frequency data in finance," Quantitative Finance, Taylor & Francis Journals, vol. 3(1), pages 1-14.
    7. Kim, Gunky & Silvapulle, Mervyn J. & Silvapulle, Paramsothy, 2007. "Comparison of semiparametric and parametric methods for estimating copulas," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2836-2850, March.
    8. Jean-David FERMANIAN & Olivier SCAILLET, 2003. "Nonparametric Estimation of Copulas for Time Series," FAME Research Paper Series rp57, International Center for Financial Asset Management and Engineering.
    9. repec:sae:ecolab:v:16:y:2006:i:2:p:1-2 is not listed on IDEAS
    10. 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.
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