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The dynamic dependence between stock markets in the greater China economic area: a study based on extreme values and copulas

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  • Saiful Izzuan Hussain

    (Universiti Kebangsaan Malaysia)

  • Steven Li

    (RMIT University)

Abstract

This study employs the dynamic copula method and extreme value theory to investigate the dependence structure between pairs of greater China economic area (GCEA) stock markets consisting of Shanghai (SHSE), Shenzhen (SZSE), Hong Kong (HKSE), and Taiwan (TWSE) stock exchanges from July 2000 to June 2017. We also examine the impact of financial crisis on the dependence structure by considering the global financial crisis and the Chinese stock market crash (2015–2016). Many studies have shown that the benefits of portfolio diversification across the stock markets in the same region could be diminishing. However, it is interesting to see that the diversification benefits appear to be viable for investing in some GCEA pairs of stock markets (SHSE–TWSE and SZSE–HKSE).

Suggested Citation

  • Saiful Izzuan Hussain & Steven Li, 2018. "The dynamic dependence between stock markets in the greater China economic area: a study based on extreme values and copulas," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(2), pages 207-233, May.
    • Handle: RePEc:kap:fmktpm:v:32:y:2018:i:2:d:10.1007_s11408-018-0308-5
    DOI: 10.1007/s11408-018-0308-5
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    1. Hussain, Saiful Izzuan & Li, Steven, 2015. "Modeling the distribution of extreme returns in the Chinese stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 34(C), pages 263-276.
    2. Chen, Xiaohong & Fan, Yanqin, 2006. "Estimation of copula-based semiparametric time series models," Journal of Econometrics, Elsevier, vol. 130(2), pages 307-335, February.
    3. Cheung, Yin-Wong & Chinn, Menzie David & Fujii, Eiji, 2003. "China, Hong Kong, and Taiwan: A Quantitative Assessment of Real and Financial Integration," Santa Cruz Department of Economics, Working Paper Series qt13d9m8jv, Department of Economics, UC Santa Cruz.
    4. Groenwold, Nicolaas & Tang, Sam Hak Kan & Wu, Yanrui, 2004. "The dynamic interrelationships between the greater China share markets," China Economic Review, Elsevier, vol. 15(1), pages 45-62, January.
    5. Nguyen, Cuong C. & Bhatti, M. Ishaq, 2012. "Copula model dependency between oil prices and stock markets: Evidence from China and Vietnam," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(4), pages 758-773.
    6. T. Ane & C. Labidi, 2006. "Spillover effects and conditional dependence," Post-Print hal-00170818, HAL.
    7. Kin‐Yip Ho & Zhaoyong Zhang, 2012. "Dynamic Linkages among Financial Markets in the Greater China Region: A Multivariate Asymmetric Approach," The World Economy, Wiley Blackwell, vol. 35(4), pages 500-523, April.
    8. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
    9. Yin-Wong Cheung & Menzie D. Chinn & Eiji Fujii, 2005. "Dimensions of financial integration in Greater China: money markets, banks and policy effects," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 10(2), pages 117-132.
    10. Hwahsin Cheng & John Glascock, 2005. "Dynamic Linkages Between the Greater China Economic Area Stock Markets—Mainland China, Hong Kong, and Taiwan," Review of Quantitative Finance and Accounting, Springer, vol. 24(4), pages 343-357, June.
    11. Ane, Thierry & Labidi, Chiraz, 2006. "Spillover effects and conditional dependence," International Review of Economics & Finance, Elsevier, vol. 15(4), pages 417-442.
    12. Cheung, Yin-Wong & Chinn, Menzie D. & Fujii, Eiji, 2003. "China, Hong Kong, and Taiwan: A quantitative assessment of real and financial integration," China Economic Review, Elsevier, vol. 14(3), pages 281-303.
    13. Nguyen, Cuong & Ishaq Bhatti, M. & Henry, Darren, 2017. "Are Vietnam and Chinese stock markets out of the US contagion effect in extreme events?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 480(C), pages 10-21.
    14. repec:adr:anecst:y:2000:i:60:p:10 is not listed on IDEAS
    15. Al Rahahleh, Naseem & Bhatti, M. Ishaq & Adeinat, Iman, 2017. "Tail dependence and information flow: Evidence from international equity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 319-329.
    16. Hyde, Stuart J & Bredin, Don P & Nguyen, Nghia, 2007. "Correlation dynamics between Asia-Pacific, EU and US stock returns," MPRA Paper 9681, University Library of Munich, Germany.
    17. Bhatti, M. Ishaq & Nguyen, Cuong C., 2012. "Diversification evidence from international equity markets using extreme values and stochastic copulas," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(3), pages 622-646.
    18. Jon Danielsson & Casper G. De Vries, 2000. "Value-at-Risk and Extreme Returns," Annals of Economics and Statistics, GENES, issue 60, pages 239-270.
    19. Kuan-Min Wang, 2013. "Did Vietnam stock market avoid the “contagion risk” from China and the U.S.? The contagion effect test with dynamic correlation coefficients," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(4), pages 2143-2161, June.
    20. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    21. Engle, Robert F & Ng, Victor K, 1993. "Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    22. Kristin J. Forbes & Roberto Rigobon, 2002. "No Contagion, Only Interdependence: Measuring Stock Market Comovements," Journal of Finance, American Finance Association, vol. 57(5), pages 2223-2261, October.
    23. François Longin & Bruno Solnik, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    24. Jian Hu, 2010. "Dependence structures in Chinese and US financial markets: a time-varying conditional copula approach," Applied Financial Economics, Taylor & Francis Journals, vol. 20(7), pages 561-583.
    25. Chen, Jian & Jiang, Fuwei & Li, Hongyi & Xu, Weidong, 2016. "Chinese stock market volatility and the role of U.S. economic variables," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 70-83.
    26. Longin, Francois M, 1996. "The Asymptotic Distribution of Extreme Stock Market Returns," The Journal of Business, University of Chicago Press, vol. 69(3), pages 383-408, July.
    27. Xiaoqing Eleanor Xu & Hung–Gay Fung, 2002. "Information Flows across Markets: Evidence from China–Backed Stocks Dual–Listed in Hong Kong and New York," The Financial Review, Eastern Finance Association, vol. 37(4), pages 563-588, November.
    28. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    29. Paul Embrechts & Sidney Resnick & Gennady Samorodnitsky, 1999. "Extreme Value Theory as a Risk Management Tool," North American Actuarial Journal, Taylor & Francis Journals, vol. 3(2), pages 30-41.
    30. Kuan-Min Wang & Thanh-Binh Nguyen Thi, 2013. "Did China avoid the ‘Asian flu’? The contagion effect test with dynamic correlation coefficients," Quantitative Finance, Taylor & Francis Journals, vol. 13(3), pages 471-481, February.
    31. Al Rahahleh, Naseem & Bhatti, M. Ishaq, 2017. "Co-movement measure of information transmission on international equity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 119-131.
    32. Bartram, Sohnke M. & Taylor, Stephen J. & Wang, Yaw-Huei, 2007. "The Euro and European financial market dependence," Journal of Banking & Finance, Elsevier, vol. 31(5), pages 1461-1481, May.
    33. Johansson, Anders C. & Ljungwall, Christer, 2009. "Spillover Effects Among the Greater China Stock Markets," World Development, Elsevier, vol. 37(4), pages 839-851, April.
    34. Ling Hu, 2006. "Dependence patterns across financial markets: a mixed copula approach," Applied Financial Economics, Taylor & Francis Journals, vol. 16(10), pages 717-729.
    35. Hong Li, 2007. "International linkages of the Chinese stock exchanges: a multivariate GARCH analysis," Applied Financial Economics, Taylor & Francis Journals, vol. 17(4), pages 285-297.
    36. He, Hongbo & Chen, Shou & Yao, Shujie & Ou, Jinghua, 2015. "Stock market interdependence between China and the world: A multi-factor R-squared approach," Finance Research Letters, Elsevier, vol. 13(C), pages 125-129.
    37. Fermanian, Jean-David, 2005. "Goodness-of-fit tests for copulas," Journal of Multivariate Analysis, Elsevier, vol. 95(1), pages 119-152, July.
    38. Rodriguez, Juan Carlos, 2007. "Measuring financial contagion: A Copula approach," Journal of Empirical Finance, Elsevier, vol. 14(3), pages 401-423, June.
    39. Wang, Kehluh & Chen, Yi-Hsuan & Huang, Szu-Wei, 2011. "The dynamic dependence between the Chinese market and other international stock markets: A time-varying copula approach," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 654-664, October.
    40. Wang, Yuenan & Iorio, Amalia Di, 2007. "Are the China-related stock markets segmented with both world and regional stock markets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 17(3), pages 277-290, July.
    41. Ser-Huang Poon, 2004. "Extreme Value Dependence in Financial Markets: Diagnostics, Models, and Financial Implications," The Review of Financial Studies, Society for Financial Studies, vol. 17(2), pages 581-610.
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    Cited by:

    1. Hussain, Saiful Izzuan & Nur-Firyal, R. & Ruza, Nadiah, 2022. "Linkage transitions between oil and the stock markets of countries with the highest COVID-19 cases," Journal of Commodity Markets, Elsevier, vol. 28(C).
    2. Saiful Izzuan Hussain & Steven Li, 2022. "Dependence structure between oil and other commodity futures in China based on extreme value theory and copulas," The World Economy, Wiley Blackwell, vol. 45(1), pages 317-335, January.
    3. Jiang, Cuixia & Ding, Xiaoyi & Xu, Qifa & Tong, Yongbo, 2020. "A TVM-Copula-MIDAS-GARCH model with applications to VaR-based portfolio selection," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).

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    More about this item

    Keywords

    Copula; Extreme value theory; Dependence structure; Chinese stock markets; Financial crisis;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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