IDEAS home Printed from https://ideas.repec.org/a/ids/ijecbr/v14y2017i3-4p390-400.html
   My bibliography  Save this article

A cellular automata model for safe investment based on expert's recommendations

Author

Listed:
  • Tessy Mathew
  • L. Jeganathan
  • U. Srinivasa Rao

Abstract

Traditional stock trading methodologies (ARMA, ARIMA, regression, etc.) are used to analyse price behaviour and then produce signals namely BUY, SELL or HOLD. Our proposed work is to develop a one-dimensional cellular automata model that helps new investors who have zero knowledge on stock market trades. The one-dimensional cellular automata (1D CA) model processes the existing recommendations or advices from the experts who possess a very good knowledge on stock market trades. Based on different expert recommendations, the CA model will give financial alerts that will help the investor to take buy/hold/sell decision on stocks. Hence new investors can either make a profit or at least keep them in safe zone (minimum loss). The trading rules in this model give highest priority to sell the share and lowest priority to buy the share. This model gives recommendations to investors regarding the selling, buying and holding of a stock/stock segment.

Suggested Citation

  • Tessy Mathew & L. Jeganathan & U. Srinivasa Rao, 2017. "A cellular automata model for safe investment based on expert's recommendations," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 14(3/4), pages 390-400.
    • Handle: RePEc:ids:ijecbr:v:14:y:2017:i:3/4:p:390-400
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=87524
    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.

    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:ids:ijecbr:v:14:y:2017:i:3/4:p:390-400. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=310 .

    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.