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Asymmetric extreme interdependence in emerging equity markets

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  • Beatriz Vaz de Melo Mendes

Abstract

We assess the extent of integration between stock markets during stressful periods using the concept of copulas. Our methodology consists of fitting copulas to simultaneous exceedances of high thresholds, and computing copula‐based measures of interdependence and contagion. Using 21 pairs of emerging stock markets daily returns, we investigate if dependence increases with crisis, and analyse the chances of both markets crashing together. Dependence at joint positive and negative extreme returns levels may differ. This type of asymmetry is captured by the upper and lower tail dependence coefficients. Propagation of crisis may be faster in one direction, and this feature is captured by asymmetric copulas. Copyright © 2005 John Wiley & Sons, Ltd.

Suggested Citation

  • Beatriz Vaz de Melo Mendes, 2005. "Asymmetric extreme interdependence in emerging equity markets," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 21(6), pages 483-498, November.
    • Handle: RePEc:wly:apsmbi:v:21:y:2005:i:6:p:483-498
    DOI: 10.1002/asmb.602
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    Cited by:

    1. Karmakar, Madhusudan, 2017. "Dependence structure and portfolio risk in Indian foreign exchange market: A GARCH-EVT-Copula approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 64(C), pages 275-291.
    2. Mudakkar, Syeda Rabab & Uppal, Jamshed Y., 2018. "Stability of cross-market bivariate return distributions during financial turbulence," Research in International Business and Finance, Elsevier, vol. 45(C), pages 389-401.
    3. Aloui, Riadh & Aïssa, Mohamed Safouane Ben & Nguyen, Duc Khuong, 2011. "Global financial crisis, extreme interdependences, and contagion effects: The role of economic structure?," Journal of Banking & Finance, Elsevier, vol. 35(1), pages 130-141, January.
    4. Krämer, Walter & van Kampen, Maarten, 2011. "A simple nonparametric test for structural change in joint tail probabilities," Economics Letters, Elsevier, vol. 110(3), pages 245-247, March.
    5. Aloui, Riadh & Aïssa, Mohamed Safouane Ben & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2014. "Dependence and extreme dependence of crude oil and natural gas prices with applications to risk management," Energy Economics, Elsevier, vol. 42(C), pages 332-342.
    6. repec:mth:ijafr8:v:9:y:2019:i:1:p:414-431 is not listed on IDEAS
    7. Karmakar, Madhusudan & Paul, Samit, 2019. "Intraday portfolio risk management using VaR and CVaR:A CGARCH-EVT-Copula approach," International Journal of Forecasting, Elsevier, vol. 35(2), pages 699-709.
    8. Garg, Jyoti & Karmakar, Madhusudan & Paul, Samit, 2023. "A study on equity home bias using vine copula approach," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    9. Sunil S. Poshakwale & Anandadeep Mandal, 2017. "Sources of time varying return comovements during different economic regimes: evidence from the emerging Indian equity market," Review of Quantitative Finance and Accounting, Springer, vol. 48(4), pages 859-892, May.
    10. Dobrić, Jadran & Frahm, Gabriel & Schmid, Friedrich, 2007. "Dependence of stock returns in bull and bear markets," Discussion Papers in Econometrics and Statistics 9/07, University of Cologne, Institute of Econometrics and Statistics.
    11. Joscha Beckmann & Theo Berger & Robert Czudaj, 2016. "Oil price and FX-rates dependency," Quantitative Finance, Taylor & Francis Journals, vol. 16(3), pages 477-488, March.
    12. Tong, Bin & Wu, Chongfeng & Zhou, Chunyang, 2013. "Modeling the co-movements between crude oil and refined petroleum markets," Energy Economics, Elsevier, vol. 40(C), pages 882-897.

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