IDEAS home Printed from https://ideas.repec.org/a/taf/apfiec/v14y2004i11p785-797.html
   My bibliography  Save this article

The Chinese stock exchange market: operations and efficiency

Author

Listed:
  • H. R. Seddighi
  • W. Nian

Abstract

The Chinese stock market has developed rapidly since early 1990s, when the two stock exchanges, the Shanghai Securities Exchange and the Shenzhen Securities Exchange, were established. Until 2000, the number of listed domestic companies has reached over 1000, and market capitalization relative to GDP reached about 33.4%. As China joins WTO, the Chinese stock market will become a great concern of the global investors, and will play a more important role in the world economy. The purpose of this paper is to provide an up-to-data account of the Chinese stock exchange market and to test its efficiency. The daily data of the Shanghai Stock Exchange index and eight shares listed in the Shanghai Stock Exchanges are examined, for this purpose. The testing procedure involves three processes: (1) use the Durbin-Watson test, Durbin 'h' test, the Lagrange Multiplier test for autocorrelation to examine the assumption of the model that the successive occurrences are independent; (2) use the Dickey-Fuller tests for unit root to test the assumption that the occurrences are identically distributed; (3) use ARCH test to examine whether the residuals contain some hidden, possibly non-linear structure, and fit a GARCH-M(1,1) model to the first difference if the ARCH effect is found to be present in the share prices.

Suggested Citation

  • H. R. Seddighi & W. Nian, 2004. "The Chinese stock exchange market: operations and efficiency," Applied Financial Economics, Taylor & Francis Journals, vol. 14(11), pages 785-797.
  • Handle: RePEc:taf:apfiec:v:14:y:2004:i:11:p:785-797
    DOI: 10.1080/0960310042000180826
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/0960310042000180826
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. C. James Hueng, 2006. "Short-sales constraints and stock return asymmetry: evidence from the Chinese stock markets," Applied Financial Economics, Taylor & Francis Journals, vol. 16(10), pages 707-716.
    2. Charles, Amélie & Darné, Olivier, 2009. "The random walk hypothesis for Chinese stock markets: Evidence from variance ratio tests," Economic Systems, Elsevier, vol. 33(2), pages 117-126, June.
    3. Hung, Jui-Cheng, 2009. "Deregulation and liberalization of the Chinese stock market and the improvement of market efficiency," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 843-857, August.
    4. Bellonia Antonella & Passaretti Tommaso & Visconti Raffaele, 2013. "Seasonality in Equity Rising on Stock Markets. Windows of Opportunity? Empirical Evidence from China, India, Brazil and South Africa," Journal of Knowledge Management, Economics and Information Technology, ScientificPapers.org, vol. 3(4), pages 1-1, August.
    5. Fifield, Suzanne G.M. & Jetty, Juliana, 2008. "Further evidence on the efficiency of the Chinese stock markets: A note," Research in International Business and Finance, Elsevier, vol. 22(3), pages 351-361, September.
    6. Long, Wen & Mok, Henry M.K. & Hu, Yan & Wang, Huiwen, 2009. "The style and innate structure of the stock markets in China," Pacific-Basin Finance Journal, Elsevier, vol. 17(2), pages 224-242, April.
    7. repec:ebl:ecbull:v:7:y:2007:i:9:p:1-12 is not listed on IDEAS
    8. Hoque, Hafiz A.A.B. & Kim, Jae H. & Pyun, Chong Soo, 2007. "A comparison of variance ratio tests of random walk: A case of Asian emerging stock markets," International Review of Economics & Finance, Elsevier, vol. 16(4), pages 488-502.
    9. Gourishankar S Hiremath & Bandi Kamaiah, 2010. "Nonlinear Dependence in Stock Returns: Evidences from India," Journal of Quantitative Economics, The Indian Econometric Society, vol. 8(1), pages 69-85, January.
    10. Vinodh Madhavan, 2014. "Investigating the nature of nonlinearity in Indian Exchange Traded Funds (ETFs)," Managerial Finance, Emerald Group Publishing, vol. 40(4), pages 395-415, March.
    11. Bodeutsch, D.S. & Franses, Ph.H.B.F., 2014. "The Stock Exchange of Suriname: Returns, Volatility, Correlations and Weak-form Efficiency," Econometric Institute Research Papers EI 2014-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:apfiec:v:14:y:2004:i:11:p:785-797. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Chris Longhurst). General contact details of provider: http://www.tandfonline.com/RAFE20 .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.