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How long memory in volatility affects true dependence structure

  • de Melo Mendes, Beatriz Vaz
  • Kolev, Nikolai
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    Long memory in volatility is a stylized fact found in most financial return series. This paper empirically investigates the extent to which interdependence in emerging markets may be driven by conditional short and long range dependence in volatility. We fit copulas to pairs of raw and filtered returns, analyse the observed changes in the dependence structure may be driven by volatility, and discuss whether or not asymmetries on propagation of crisis may be interpreted as intrinsic characteristics of the markets. We also use the findings to construct portfolios possessing desirable expected behavior such as dependence at extreme positive levels.

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    File URL: http://www.sciencedirect.com/science/article/B6W4W-4P7R8D6-1/2/156d142105e8f7be3d9561430f45651d
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    Article provided by Elsevier in its journal International Review of Financial Analysis.

    Volume (Year): 17 (2008)
    Issue (Month): 5 (December)
    Pages: 1070-1086

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    Handle: RePEc:eee:finana:v:17:y:2008:i:5:p:1070-1086
    Contact details of provider: Web page: http://www.elsevier.com/locate/inca/620166

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    1. Roger Nelsen, 2007. "Extremes of nonexchangeability," Statistical Papers, Springer, vol. 48(4), pages 695-695, October.
    2. Thierry Ane & Cecile Kharoubi, 2003. "Dependence Structure and Risk Measure," The Journal of Business, University of Chicago Press, vol. 76(3), pages 411-438, July.
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    5. Breidt, F. Jay & Crato, Nuno & de Lima, Pedro, 1998. "The detection and estimation of long memory in stochastic volatility," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 325-348.
    6. Bollerslev, Tim & Wright, Jonathan H., 2000. "Semiparametric estimation of long-memory volatility dependencies: The role of high-frequency data," Journal of Econometrics, Elsevier, vol. 98(1), pages 81-106, September.
    7. François Longin, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, 04.
    8. Sadique, Shibley & Silvapulle, Param, 2001. "Long-Term Memory in Stock Market Returns: International Evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 6(1), pages 59-67, January.
    9. 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.
    10. Granger, C. W. J., 1980. "Long memory relationships and the aggregation of dynamic models," Journal of Econometrics, Elsevier, vol. 14(2), pages 227-238, October.
    11. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July.
    12. Ding, Zhuanxin & Granger, Clive W. J., 1996. "Modeling volatility persistence of speculative returns: A new approach," Journal of Econometrics, Elsevier, vol. 73(1), pages 185-215, July.
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