IDEAS home Printed from https://ideas.repec.org/a/hin/jnddns/7957282.html
   My bibliography  Save this article

Evolutionary Game Model of Stock Price Synchronicity from Investor Behavior

Author

Listed:
  • Yue Dong
  • Yuhao Zhang
  • Jinnan Pan
  • Tingqiang Chen

Abstract

Institutional and individual investors are the two important players in the stock market. Together, they determine the price of the stock market. In this paper, an evolutionary game model that contains the two groups of players is proposed to analyze the stock price synchronicity considering the impacts of investors’ decisions on stock investment. Factors affecting investors’ decisions include the potential revenue or loss, the probability of gain or loss, and the cost of corresponding behavior. The proposed game model is analyzed by replicator dynamics equations and simulation of the evolutionary equilibrium strategy under different circumstances. The analysis shows that the operating cost of institutional investors, the cost of information collection before trading, and the expected loss that may be punished by regulators are the key factors that affect the evolutionary game system between institutional investors and individual investors. In addition, reducing the speculation in the market and increasing the information access of investors through the serious operation mode of institutional investors and the strengthening of the market information disclosure mechanism are beneficial to alleviate price synchronicity in stock market.

Suggested Citation

  • Yue Dong & Yuhao Zhang & Jinnan Pan & Tingqiang Chen, 2020. "Evolutionary Game Model of Stock Price Synchronicity from Investor Behavior," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-9, February.
  • Handle: RePEc:hin:jnddns:7957282
    DOI: 10.1155/2020/7957282
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/DDNS/2020/7957282.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/DDNS/2020/7957282.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2020/7957282?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
    ---><---

    Citations

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


    Cited by:

    1. Guo, Jian & Zhong, Minghao & Chen, Shuran, 2022. "Analysis and simulation of BECCS vertical integration model in China based on evolutionary game and system dynamics," Energy, Elsevier, vol. 252(C).

    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:hin:jnddns:7957282. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.