IDEAS home Printed from https://ideas.repec.org/a/ids/ijbire/v19y2019i3p285-303.html
   My bibliography  Save this article

Financial interval time series modelling and forecasting using threshold autoregressive models

Author

Listed:
  • Leandro Maciel

Abstract

Financial interval time series (ITS) describe the evolution of the high and low prices of an asset throughout time. Their accurate forecasts play a key role in risk management, derivatives pricing and asset allocation, demanding the development of models able to properly predict these prices. This paper evaluates threshold autoregressive models for financial ITS forecasting as a nonlinear approach for ITS considering as empirical application the main index of the Brazilian stock market, the IBOVESPA. One step ahead interval forecasts are compared against linear and nonlinear time series benchmark methods in terms of traditional accuracy metrics and quality measures designed for ITS. The results indicated the predictability of IBOVESPA ITS and that significant forecast contribution are achieved when nonlinear approaches are considered. Further, nonlinear models do provide higher accuracy when forecasting Brazilian financial ITS.

Suggested Citation

  • Leandro Maciel, 2019. "Financial interval time series modelling and forecasting using threshold autoregressive models," International Journal of Business Innovation and Research, Inderscience Enterprises Ltd, vol. 19(3), pages 285-303.
    • Handle: RePEc:ids:ijbire:v:19:y:2019:i:3:p:285-303
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=100323
    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:ijbire:v:19:y:2019:i:3:p:285-303. 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=203 .

    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.