IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v64y2024i6d10.1007_s10614-024-10580-x.html
   My bibliography  Save this article

Estimation of Models for Stock Returns

Author

Listed:
  • Saralees Nadarajah

    (University of Manchester)

  • Thomas Hitchen

    (University of Manchester)

Abstract

Composite distributions where volatility itself is assumed to be a random variable have been used to model stock returns. In this paper, we give details of estimation of these composite distributions when the volatility is assumed to follow an arbitrary distribution and the conditional distribution of stock returns given the volatility follows one of normal, Laplace, uniform, Student’s t, Cauchy, logistic of type I, logistic of type II, logistic of type III, logistic of type IV, generalized normal or skew normal distributions. The details given include estimating equations and observed information matrices. An application to Bitcoin exchange rate data is illustrated. Models taking volatility to follow gamma and Weibull distributions are shown to provide excellent fits.

Suggested Citation

  • Saralees Nadarajah & Thomas Hitchen, 2024. "Estimation of Models for Stock Returns," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3577-3616, December.
    • Handle: RePEc:kap:compec:v:64:y:2024:i:6:d:10.1007_s10614-024-10580-x
    DOI: 10.1007/s10614-024-10580-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10614-024-10580-x
    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/s10614-024-10580-x?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:kap:compec:v:64:y:2024:i:6:d:10.1007_s10614-024-10580-x. 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.