IDEAS home Printed from https://ideas.repec.org/a/bpj/statpp/v13y2022i2p235-254n4.html
   My bibliography  Save this article

Bayesian Switching Volatility Models for Analysing Stock Returns in Ghana

Author

Listed:
  • Akurugu Edward

    (Department of Statistics, Faculty of Mathematical Sciences, University for Development Studies, Tamale, Ghana)

  • Angbing Irene Dekomwine
  • Nasiru Suleman
  • Abubakari Abdul Ghaniyyu

    (Department of Statistics, School of Mathematical Sciences, C. K. Tedam University of Technology and Applied Sciences, Navrongo, Ghana)

Abstract

The goal of this research was to use Bayesian switching volatility models to model the stock returns of the GCB, bank in Ghana. Monthly stock prices of GCB bank for the period of 138 months were used for the study. The two-state Markov-Switching GARCH models were used in the study to determine the best model for modelling and forecasting the stock returns. The Deviance Information Criteria was considered when selecting the best model. Based on the Deviance Information Criteria, E-GARCH variance specification with skewed student-t innovation was shown to be appropriate for modelling the stock returns. The estimates of the best model showed the first regime to exhibit the features of “turbulent market conditions” while the second regime exhibits “tranquil market conditions”. The risk analysis finds the best model to generally perform better in estimating both Value-at-Risk and Expected Shortfall at 1% rather than 5%. The study advises investors to invest in GCB bank because of the high returns connected with the stock and the fact that when “turbulent market conditions” arise, the recovery rate for these stocks is faster.

Suggested Citation

  • Akurugu Edward & Angbing Irene Dekomwine & Nasiru Suleman & Abubakari Abdul Ghaniyyu, 2022. "Bayesian Switching Volatility Models for Analysing Stock Returns in Ghana," Statistics, Politics and Policy, De Gruyter, vol. 13(2), pages 235-254, June.
    • Handle: RePEc:bpj:statpp:v:13:y:2022:i:2:p:235-254:n:4
    DOI: 10.1515/spp-2022-0002
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/spp-2022-0002
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1515/spp-2022-0002?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:bpj:statpp:v:13:y:2022:i:2:p:235-254:n:4. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.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.