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Frequent Turbulence? A Dynamic Copula Approach

Author

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  • Chollete, Lorán

    (Dept. of Finance and Management Science, Norwegian School of Economics and Business Administration)

  • Heinen, Andreas

    (Dept. of Statistics and Econometrics, Universidad Carlos III de Madrid)

Abstract

How common and how persistent are turbulent periods? We address these questions by developing and applying a dynamic dependence framework. In order to answer the first question we estimate an unconditional mixture model of normal copulas, based on both economic and econometric justification. In order to answer the second question, we develop and estimate a hidden markov model of copulas, which allows for dynamic clustering of correlations. These models permit one to infer the relative importance of turbulent and quiescent periods in international markets. Empirically, the three most striking findings are as follows. First, for the unconditional model, turbulent regimes are more common. Second, the conditional copula model dominates the unconditional model. Third, turbulent regimes tend to be more persistent.

Suggested Citation

  • Chollete, Lorán & Heinen, Andreas, 2006. "Frequent Turbulence? A Dynamic Copula Approach," Discussion Papers 2006/10, Norwegian School of Economics, Department of Business and Management Science.
  • Handle: RePEc:hhs:nhhfms:2006_010
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    File URL: http://hdl.handle.net/11250/163892
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    References listed on IDEAS

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    1. William Schwert, G., 2002. "Stock volatility in the new millennium: how wacky is Nasdaq?," Journal of Monetary Economics, Elsevier, vol. 49(1), pages 3-26, January.
    2. Andrew J. Patton, 2004. "On the Out-of-Sample Importance of Skewness and Asymmetric Dependence for Asset Allocation," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 130-168.
    3. Ang, Andrew & Chen, Joseph, 2002. "Asymmetric correlations of equity portfolios," Journal of Financial Economics, Elsevier, vol. 63(3), pages 443-494, March.
    4. Rodriguez, Juan Carlos, 2007. "Measuring financial contagion: A Copula approach," Journal of Empirical Finance, Elsevier, vol. 14(3), pages 401-423, June.
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    Cited by:

    1. Penikas, Henry & Simakova, Varvara, 2009. "Interest Rate Risk Management Based on Copula-GARCH Models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 13(1), pages 3-36.
    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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    More about this item

    Keywords

    International Markets; Turbulence; Hidden Markov Model; Copula;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • F30 - International Economics - - International Finance - - - General
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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