IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1111.5254.html
   My bibliography  Save this paper

Markov Chains application to the financial-economic time series prediction

Author

Listed:
  • Vladimir Soloviev
  • Vladimir Saptsin
  • Dmitry Chabanenko

Abstract

In this research the technology of complex Markov chains is applied to predict financial time series. The main distinction of complex or high-order Markov Chains and simple first-order ones is the existing of aftereffect or memory. The technology proposes prediction with the hierarchy of time discretization intervals and splicing procedure for the prediction results at the different frequency levels to the single prediction output time series. The hierarchy of time discretizations gives a possibility to use fractal properties of the given time series to make prediction on the different frequencies of the series. The prediction results for world's stock market indices is presented.

Suggested Citation

  • Vladimir Soloviev & Vladimir Saptsin & Dmitry Chabanenko, 2011. "Markov Chains application to the financial-economic time series prediction," Papers 1111.5254, arXiv.org.
  • Handle: RePEc:arx:papers:1111.5254
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1111.5254
    File Function: Latest version
    Download Restriction: no

    Citations

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


    Cited by:

    1. Stepchenko Arthur & Chizhov Jurij, 2015. "Applying Markov Chains for NDVI Time Series Forecasting of Latvian Regions," Information Technology and Management Science, De Gruyter Open, vol. 18(1), pages 57-61, December.
    2. repec:eee:apmaco:v:303:y:2017:i:c:p:226-239 is not listed on IDEAS

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:1111.5254. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (arXiv administrators). General contact details of provider: http://arxiv.org/ .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.