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Detection of Structural Breaks in Copula Models

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Author Info

  • Brodsky, Boris

    ()
    (Central Economic-Mathematical Institute, Russia)

  • Penikas, Henry

    ()
    (Higher School of Economics, Russia)

  • Safaryan, Irina

    ()
    (Russian-Armenian (Slavonic) State University)

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    Abstract

    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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    Bibliographic Info

    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

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    Web page: http://appliedeconometrics.cemi.rssi.ru/

    Related research

    Keywords: Copula; structural break; Kolmogorov-Smirnov statistics; interest rates; MosPrime; LIBOR; EURIBOR;

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    References

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    1. 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.
    2. Y. Malevergne & D. Sornette, 2003. "Testing the Gaussian copula hypothesis for financial assets dependences," Quantitative Finance, Taylor & Francis Journals, vol. 3(4), pages 231-250.
    3. Bruno Rémillard & Olivier Scaillet, 2006. "Testing For Equality Between Two Copulas," Swiss Finance Institute Research Paper Series 07-24, Swiss Finance Institute.
    4. repec:sae:ecolab:v:16:y:2006:i:2:p:1-2 is not listed on IDEAS
    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. 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.
    8. 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.
    9. Markus Junker & Angelika May, 2005. "Measurement of aggregate risk with copulas," Econometrics Journal, Royal Economic Society, vol. 8(3), pages 428-454, December.
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    Cited by:
    1. Penikas, Henry, 2011. "Copula-Based Price Risk Hedging Models," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 22(2), pages 3-21.
    2. Penikas, H., 2010. "Financial Applications of Copula-Models," Journal of the New Economic Association, New Economic Association, issue 7, pages 24-44.

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