IDEAS home Printed from https://ideas.repec.org/a/spr/metron/v82y2024i3d10.1007_s40300-024-00275-6.html
   My bibliography  Save this article

A Bayes analysis of autoregressive model having functional-coefficients and its application on exchange rate data

Author

Listed:
  • Praveen Kumar Tripathi

    (Banasthali Vidyapith)

  • Manika Agarwal

    (Banasthali Vidyapith)

  • Satyanshu K. Upadhyay

    (Banaras Hindu University)

Abstract

The paper provides a Bayes analysis, based on free-knot spline technique, of the popular autoregressive model having functional-coefficients. The model was initially proposed by Chen and Tsay (1993). The technique of polynomial splines of different orders is used to approximate the functional-coefficients. A sample based approach using the Gibbs sampler algorithm with intermediate Metropolis steps is adopted to draw the posterior estimates for the parameters involved. Additionally, the technique of reversible jump Markov chain Monte Carlo is incorporated to update the location and number of knots in the polynomial spline. The paper then proceeds with the motive of obtaining both retrospective and prospective predictions based on the selected model. The complete procedure is illustrated by both simulated and a real dataset representing the exchange rate of Indian rupees relative to the US dollars.

Suggested Citation

  • Praveen Kumar Tripathi & Manika Agarwal & Satyanshu K. Upadhyay, 2024. "A Bayes analysis of autoregressive model having functional-coefficients and its application on exchange rate data," METRON, Springer;Sapienza Università di Roma, vol. 82(3), pages 363-391, December.
  • Handle: RePEc:spr:metron:v:82:y:2024:i:3:d:10.1007_s40300-024-00275-6
    DOI: 10.1007/s40300-024-00275-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40300-024-00275-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s40300-024-00275-6?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:spr:metron:v:82:y:2024:i:3:d:10.1007_s40300-024-00275-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.