IDEAS home Printed from https://ideas.repec.org/a/wsi/ijmpcx/v31y2020i10ns0129183120501454.html
   My bibliography  Save this article

Regularities in stock markets

Author

Listed:
  • Abhin Kakkad

    (Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar 382007, Gujarat, India)

  • Harsh Vasoya

    (Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar 382007, Gujarat, India)

  • Arnab K. Ray

    (Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar 382007, Gujarat, India)

Abstract

From the stock markets of six countries with high GDP, we study the stock indices, S&P 500 (NYSE, USA), SSE Composite (SSE, China), Nikkei (TSE, Japan), DAX (FSE, Germany), FTSE 100 (LSE, Britain) and NIFTY (NSE, India). The daily mean growth of the stock values is exponential. The daily price fluctuations about the mean growth are Gaussian, but with a nonzero asymptotic convergence. The growth of the monthly average of stock values is statistically self-similar to their daily growth. The monthly fluctuations of the price follow a Wiener process, with a decline of the volatility. The mean growth of the daily volume of trade is exponential. These observations are globally applicable and underline regularities across global stock markets.

Suggested Citation

  • Abhin Kakkad & Harsh Vasoya & Arnab K. Ray, 2020. "Regularities in stock markets," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 31(10), pages 1-9, October.
    • Handle: RePEc:wsi:ijmpcx:v:31:y:2020:i:10:n:s0129183120501454
    DOI: 10.1142/S0129183120501454
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0129183120501454
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0129183120501454?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.

    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:wsi:ijmpcx:v:31:y:2020:i:10:n:s0129183120501454. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijmpc/ijmpc.shtml .

    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.