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Stock Returns and Volatility: an empirical study of Chinese stock markets

Author

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  • Haiyan Song
  • Xiaming Liu
  • Peter Romilly

Abstract

This paper uses GARCH models to analyse the relationship between returns and volatility on the Shanghai and Shenzhen Stock Exchanges in China. Empirical estimates using the sample data from 21 May 1992 to 2 February 1996 suggest that the variances of the returns in the two markets are best modeled by the GARCH-M (1,1) specification. Volatility transmission between the two markets (the volatility spill-over effect) is also found to exist. The results of one month ahead ex ante forecasts show that the conditional variances of the returns of the two stock markets exhibit a similar pattern.

Suggested Citation

  • Haiyan Song & Xiaming Liu & Peter Romilly, 1998. "Stock Returns and Volatility: an empirical study of Chinese stock markets," International Review of Applied Economics, Taylor & Francis Journals, vol. 12(1), pages 129-139.
    • Handle: RePEc:taf:irapec:v:12:y:1998:i:1:p:129-139
    DOI: 10.1080/026921719800000029
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    Citations

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    Cited by:

    1. Syed Kumail Abbas Rizvi & Bushra Naqvi & Nawazish Mirza, 2022. "Is green investment different from grey? Return and volatility spillovers between green and grey energy ETFs," Annals of Operations Research, Springer, vol. 313(1), pages 495-524, June.
    2. W.C Lo & W.S. Chan, 2000. "Diagnosing Shocks in Stock Market Returns of Greater China," Multinational Finance Journal, Multinational Finance Journal, vol. 4(3-4), pages 269-288, September.
    3. Ekaterini Tsouma, 2007. "Stock return dynamics and stock market interdependencies," Applied Financial Economics, Taylor & Francis Journals, vol. 17(10), pages 805-825.
    4. Wang, Zijun & Kutan, Ali M. & Yang, Jian, 2005. "Information flows within and across sectors in Chinese stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 45(4-5), pages 767-780, September.
    5. Demirer, RIza & Kutan, Ali M., 2006. "Does herding behavior exist in Chinese stock markets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 16(2), pages 123-142, April.
    6. Umar, Muhammad & Rizvi, Syed Kumail Abbas & Naqvi, Bushra, 2021. "Dance with the devil? The nexus of fourth industrial revolution, technological financial products and volatility spillovers in global financial system," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    7. Eun, Cheol S. & Huang, Wei, 2007. "Asset pricing in China's domestic stock markets: Is there a logic?," Pacific-Basin Finance Journal, Elsevier, vol. 15(5), pages 452-480, November.
    8. Xiao‐Ming Li, 2003. "China: Further Evidence on the Evolution of Stock Markets in Transition Economies," Scottish Journal of Political Economy, Scottish Economic Society, vol. 50(3), pages 341-358, August.
    9. Ioannis A. Tampakoudis & Demetres N. Subeniotis & Ioannis G. Kroustalis, 2012. "Modelling volatility during the current financial crisis: an empirical analysis of the US and the UK stock markets," International Journal of Trade and Global Markets, Inderscience Enterprises Ltd, vol. 5(3/4), pages 171-194.
    10. Habibullah, M.S. & Baharom, A.H. & Fong, Kin Hing, 2009. "Predictive Content of Output and Inflation For Stock Returns and Volatility: Evidence from Selected Asian Countries," MPRA Paper 14114, University Library of Munich, Germany.
    11. Poon, Winnie P. H. & Fung, Hung-Gay, 2000. "Red chips or H shares: which China-backed securities process information the fastest?," Journal of Multinational Financial Management, Elsevier, vol. 10(3-4), pages 315-343, December.

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