IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-94-6463-298-9_59.html

An Empirical Research of Seasonality in Chinese Stock Markets

In: Proceedings of the 2023 International Conference on Finance, Trade and Business Management (FTBM 2023)

Author

Listed:
  • Jiaxi Sun

    (Southern University of Science and Technology, Business School)

Abstract

Due to the expansion of the Chinese financial market, the characteristics and influencing factors of the Chinese stock market, including seasonality, have received increasing attention from researchers. This article covers the researchers’ use of several techniques to examine the stock market’s seasonality at various temporal and geographic scales, and then investigates the seasonality in the Chinese stock market. In order to focus on relatively stable stock market data, this article selected A-share data from January 1, 2011, to December 31, 2022 in the CSMAR database. The paper firstly used descriptive statistical methods to study the relationship between monthly average return rate over the entire study period and the average return rate of all data, as well as the relationship between the monthly returns and their volatility. To study the seasonality and volatility, this paper used ARIMA(1,1,1)-GARCH(1,1) model, which has good data match. The results of running these models show that there is a monthly effect in the Chinese market caused by Lunar New Year. Chinese stock markets do not have half-year effect. These results indicate that cultural and structural factors are important in shaping the seasonality of the Chinese stock market. Even considering the associated risks and uncertainties, trading strategies regarding seasonality in the stock market may still bring attractive returns.

Suggested Citation

  • Jiaxi Sun, 2023. "An Empirical Research of Seasonality in Chinese Stock Markets," Advances in Economics, Business and Management Research, in: Amalendu Bhunia & Rubi Binti Ahmad & Yifeng Zhu (ed.), Proceedings of the 2023 International Conference on Finance, Trade and Business Management (FTBM 2023), pages 544-551, Springer.
  • Handle: RePEc:spr:advbcp:978-94-6463-298-9_59
    DOI: 10.2991/978-94-6463-298-9_59
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;

    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:spr:advbcp:978-94-6463-298-9_59. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.