IDEAS home Printed from https://ideas.repec.org/a/idp/bizinf/y2014i1p114_117.html
   My bibliography  Save this article

Development of a Model of Knowledge Mining for Forecasting Financial Markets with Allocation of Standard Tendencies from the Time Series

Author

Listed:
  • Nykytenko Oleksiy K.

    (The National Metallurgical Academy of Ukraine)

Abstract

The article develops a model of knowledge mining for forecasting financial markets with allocation of standard tendencies from the time series. The model is considered from the point of view of application of the Knowledge Mining technology. The article provides solution of the direct and inverse problems of adequacy of processing economic information within the framework of acquisition of the formal feature of metricity in the process of the model application. The article shows that due to optimisation the models on the educational sampling of knowledge acquire the notional component, that is the semantic feature. The article offers ways of assessing characteristics of consistency and fullness for ensuring knowledge with a formal feature of activity. The feature of knowledge coherence is included into the fullness characteristic.

Suggested Citation

  • Nykytenko Oleksiy K., 2014. "Development of a Model of Knowledge Mining for Forecasting Financial Markets with Allocation of Standard Tendencies from the Time Series," Business Inform, RESEARCH CENTRE FOR INDUSTRIAL DEVELOPMENT PROBLEMS of NAS (KHARKIV, UKRAINE), Kharkiv National University of Economics, issue 1, pages 114-117.
  • Handle: RePEc:idp:bizinf:y:2014:i:1:p:114_117
    as

    Download full text from publisher

    File URL: https://www.business-inform.net/pdf/2014/1_0/114_117.pdf
    Download Restriction: no
    ---><---

    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:idp:bizinf:y:2014:i:1:p:114_117. 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: Khaustova Viktoriia (email available below). General contact details of provider: https://www.business-inform.net .

    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.