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Conditional dependence between international stock markets: A long memory GARCH-copula model approach

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  • Mokni, Khaled
  • Mansouri, Faysal

Abstract

In this paper, we investigate the relationship between major international stock markets by taking into account the long memory in volatility under structural shifts. We use long memory GARCH-skewed student-t models for the marginal distribution modeling and copulas functions for the dependence structure investigation. Using daily international stock market data from 2003 to 2017, the empirical results show that the long memory GARCH-copula models are more appropriate than standard GARCH-copulas models in dependence modeling. Moreover, results indicate that the dependence structure increases during the global financial and European debt crisis. Furthermore, a Value-at-Risk application shows that the long memory GARCH-copula models provide more accurate multivariate market risk estimation. Therefore, the dependence structure between stock markets is affected by long memory in volatility. These findings have important implications for investors interested in international stock markets for portfolio diversification, risk management, and international asset allocation.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:mulfin:v:42-43:y:2017:i::p:116-131
    DOI: 10.1016/j.mulfin.2017.10.006
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    Cited by:

    1. Mokni, Khaled & Youssef, Manel, 2019. "Measuring persistence of dependence between crude oil prices and GCC stock markets: A copula approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 72(C), pages 14-33.
    2. Khaled Mokni, 2018. "Empirical Analysis Of The Relationship Between Oil And Precious Metals Markets," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(01), pages 1-20, March.
    3. Charfeddine, Lanouar & Al Refai, Hisham, 2019. "Political tensions, stock market dependence and volatility spillover: Evidence from the recent intra-GCC crises," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    4. Benlagha, Noureddine, 2020. "Stock market dependence in crisis periods: Evidence from oil price shocks and the Qatar blockade," Research in International Business and Finance, Elsevier, vol. 54(C).
    5. Manel Youssef & Khaled Mokni, 2019. "Do Crude Oil Prices Drive the Relationship between Stock Markets of Oil-Importing and Oil-Exporting Countries?," Economies, MDPI, Open Access Journal, vol. 7(3), pages 1-22, July.
    6. Manel Youssef & Khaled Mokni & Ahdi Noomen Ajmi, 2021. "Dynamic connectedness between stock markets in the presence of the COVID-19 pandemic: does economic policy uncertainty matter?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.

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    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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