IDEAS home Printed from https://ideas.repec.org/a/taf/jbemgt/v15y2014i4p744-775.html
   My bibliography  Save this article

Intertemporal portfolio allocation and hedging demand: an application to South Africa

Author

Listed:
  • Esti Van Wyk de Vries
  • Rangan Gupta
  • Reneé Van Eyden

Abstract

This paper analyses the intertemporal hedging demand for stocks and bonds in South Africa, the United Kingdom and the United States. The analysis is done using an approximate solution method for the optimal consumption and wealth portfolio problem of an infinitely long-lived investor. Investors are assumed to have Epstein-Zin-Weil-type preferences and face asset returns described by a first-order vector autoregression in returns and state variables. The results show that the mean intertemporal hedging demands for stocks are considerably smaller in SA than in the UK or the US, whilst the mean intertemporal hedging demand for bonds are not significantly different from zero in any of the countries considered. Furthermore, it is found that stocks in the US and the UK do not present a useful hedging opportunity for an investor in SA, nor do SA stocks present a useful hedging opportunity for investors from the UK or the US.

Suggested Citation

  • Esti Van Wyk de Vries & Rangan Gupta & Reneé Van Eyden, 2014. "Intertemporal portfolio allocation and hedging demand: an application to South Africa," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 15(4), pages 744-775, September.
    • Handle: RePEc:taf:jbemgt:v:15:y:2014:i:4:p:744-775
    DOI: 10.3846/16111699.2012.688855
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.3846/16111699.2012.688855
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.3846/16111699.2012.688855?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 look for a different version below or search for a different version of it.

    Other versions of this item:

    Citations

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


    Cited by:

    1. Ali Babikir & Henry Mwambi, 2016. "Evaluating the combined forecasts of the dynamic factor model and the artificial neural network model using linear and nonlinear combining methods," Empirical Economics, Springer, vol. 51(4), pages 1541-1556, December.
    2. Spierdijk, Laura & Umar, Zaghum, 2014. "Stocks for the long run? Evidence from emerging markets," Journal of International Money and Finance, Elsevier, vol. 47(C), pages 217-238.

    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    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:taf:jbemgt:v:15:y:2014:i:4:p:744-775. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TBEM20 .

    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.