IDEAS home Printed from https://ideas.repec.org/a/taf/reroxx/v33y2020i1p521-539.html
   My bibliography  Save this article

Dynamic relationship between the stock market and macroeconomy in China (1995–2018): new evidence from the continuous wavelet analysis

Author

Listed:
  • Rui Wang
  • Lianfa Li

Abstract

This article examines the relationship between the stock market and three widely used macroeconomic variables, namely industrial production growth, inflation, and long-term interest rate in China. We use the continuous wavelet analysis to investigate the correlations and lead–lag relationships between them in the time–frequency domain by covering a period of 1995M01-2018M04. Our findings show the positive relationship between stock returns and industrial production growth and between stock returns and inflation. Notably, we find that stock returns and long-term interest rate are negatively correlated in short and medium terms, while they are positively correlated in the long term. The puzzling positive correlation between stock returns and interest rate as well as the mixed lead–lag relationships suggest that the Chinese stock market is quite undeveloped. There are breakdowns of the link between the stock market and macroeconomy. Neither the stock return can be used as a leading indicator of the macroeconomy nor the real economy could predict the booms or busts of the Chinese stock market.

Suggested Citation

  • Rui Wang & Lianfa Li, 2020. "Dynamic relationship between the stock market and macroeconomy in China (1995–2018): new evidence from the continuous wavelet analysis," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 33(1), pages 521-539, January.
    • Handle: RePEc:taf:reroxx:v:33:y:2020:i:1:p:521-539
    DOI: 10.1080/1331677X.2020.1716264
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/1331677X.2020.1716264
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/1331677X.2020.1716264?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    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:reroxx:v:33:y:2020:i:1:p:521-539. 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/rero .

    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.