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How long memory in volatility affects true dependence structure

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  • de Melo Mendes, Beatriz Vaz
  • Kolev, Nikolai

Abstract

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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  • de Melo Mendes, Beatriz Vaz & Kolev, Nikolai, 2008. "How long memory in volatility affects true dependence structure," International Review of Financial Analysis, Elsevier, vol. 17(5), pages 1070-1086, December.
    • Handle: RePEc:eee:finana:v:17:y:2008:i:5:p:1070-1086
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    2. Boubaker, Heni & Sghaier, Nadia, 2013. "Portfolio optimization in the presence of dependent financial returns with long memory: A copula based approach," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 361-377.
    3. Tripathy, Naliniprava, 2022. "Long memory and volatility persistence across BRICS stock markets," Research in International Business and Finance, Elsevier, vol. 63(C).
    4. Hayette Gatfaoui, 2010. "Investigating the dependence structure between credit default swap spreads and the U.S. financial market," Annals of Finance, Springer, vol. 6(4), pages 511-535, October.
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    8. Pece Andreea Maria & Ludusan (Corovei) Emilia Anuta & Mutu Simona, 2013. "Testing The Long Range-Dependence For The Central Eastern European And The Balkans Stock Markets," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 1113-1124, July.
    9. Rim Ammar Lamouchi, 2020. "Long Memory and Stock Market Efficiency: Case of Saudi Arabia," International Journal of Economics and Financial Issues, Econjournals, vol. 10(3), pages 29-34.
    10. Mokni, Khaled & Mansouri, Faysal, 2017. "Conditional dependence between international stock markets: A long memory GARCH-copula model approach," Journal of Multinational Financial Management, Elsevier, vol. 42, pages 116-131.
    11. Heni Boubaker & Nadia Sghaier, 2015. "On the Dynamic Dependence between US and other Developed Stock Markets: An Extreme-value Time-varying Copula Approach," Bankers, Markets & Investors, ESKA Publishing, issue 136-137, pages 80-93, May-June.
    12. R. P. C. Leal & B. V. M. Mendes, 2013. "Assessing the effect of tail dependence in portfolio allocations," Applied Financial Economics, Taylor & Francis Journals, vol. 23(15), pages 1249-1256, August.
    13. Heni Boubaker & Nadia Sghaier, 2014. "On the dynamic dependence between US and other developed stock markets: An extreme-value time-varying copula approach," Working Papers 2014-281, Department of Research, Ipag Business School.
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    15. Heni Boubaker & Nadia Sghaier, 2014. "On the dynamic dependence between US and other developed stock markets: An extreme," Working Papers 2014-94, Department of Research, Ipag Business School.

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