IDEAS home Printed from https://ideas.repec.org/a/mes/chinec/v41y2008i2p24-33.html
   My bibliography  Save this article

Testing for Structural Change in the Nontradable Share Reform of the Chinese Stock Market

Author

Listed:
  • Fang Huang
  • Jun Su
  • Terence Tai-Leung Chong

Abstract

We test for structural change in the Chinese stock-price level caused by the nontradable share (NTS) reform. Using the net-of-market-trend stock-price series, we found that the NTS reform drives stock prices up in more than two-thirds of the cases. For the twenty-oneâday window, the effect of the NTS reform is significant. Half of the stock prices have a shift right after readmission. It is also found that stocks with bonus-share distribution proportion between 15 percent and 20 percent are more likely to have a downward shift in price than those with other proportions.

Suggested Citation

  • Fang Huang & Jun Su & Terence Tai-Leung Chong, 2008. "Testing for Structural Change in the Nontradable Share Reform of the Chinese Stock Market," Chinese Economy, Taylor & Francis Journals, vol. 41(2), pages 24-33, March.
    • Handle: RePEc:mes:chinec:v:41:y:2008:i:2:p:24-33
    as

    Download full text from publisher

    File URL: http://mesharpe.metapress.com/link.asp?target=contribution&id=G030W6053K016164
    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. Beltratti, Andrea & Bortolotti, Bernardo & Caccavaio, Marianna, 2016. "Stock market efficiency in China: Evidence from the split-share reform," The Quarterly Review of Economics and Finance, Elsevier, vol. 60(C), pages 125-137.
    2. Chong, Terence Tai-Leung & Lam, Tau-Hing & Yan, Isabel Kit-Ming, 2012. "Is the Chinese stock market really inefficient?," China Economic Review, Elsevier, vol. 23(1), pages 122-137.
    3. Hong, Hui & Chen, Naiwei & O’Brien, Fergal & Ryan, James, 2018. "Stock return predictability and model instability: Evidence from mainland China and Hong Kong," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 132-142.
    4. Terence Tai-Leung Chong & Nasha Li & Lin Zou, 2017. "A New Approach to Modeling Sector Stock Returns in China," Chinese Economy, Taylor & Francis Journals, vol. 50(5), pages 305-322, September.
    5. Danli Wang & Terence Tai-Leung Chong, 2017. "Political Turnover and the Stock Performance of SOEs in China," Chinese Economy, Taylor & Francis Journals, vol. 50(1), pages 21-33, January.

    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:mes:chinec:v:41:y:2008:i:2:p:24-33. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/MCES20 .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.