IDEAS home Printed from https://ideas.repec.org/a/taf/repmxx/v5y1999i1p31-45.html
   My bibliography  Save this article

Optimal Diversification within Mixed-Asset Portfolios using a Conditional Heteroskedasticity Approach: Evidence from the U.S. and the U.K

Author

Listed:
  • Michael Giliberto
  • Foort Hamelink
  • Martin Hoesli
  • Bryan MacGregor

Abstract

Executive Summary. In this article, portfolio allocation strategies based on a threshold autoregressive conditional heteroskedasticity model (QTARCH) are constructed for the United States and the United Kingdom and compared to a conventional asset allocation. Our procedure is based on partitioning the historical data into ‘states of the world,’ which are used to produce expectations of return and risk. Several approaches are developed to partition an initial in-sample period (1978-1983), using quarterly asset returns and economic data. These partitions are then used to test out-of-sample strategies for the next quarter. Although the conditional results are sensitive to the method of partitioning, we show that the approach can improve portfolio performance in both countries and that most of the performance improvement stems from using conditional variances-covariances.

Suggested Citation

  • Michael Giliberto & Foort Hamelink & Martin Hoesli & Bryan MacGregor, 1999. "Optimal Diversification within Mixed-Asset Portfolios using a Conditional Heteroskedasticity Approach: Evidence from the U.S. and the U.K," Journal of Real Estate Portfolio Management, Taylor & Francis Journals, vol. 5(1), pages 31-45, January.
    • Handle: RePEc:taf:repmxx:v:5:y:1999:i:1:p:31-45
    DOI: 10.1080/10835547.1999.12089565
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/10835547.1999.12089565
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/10835547.1999.12089565?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.

    More about this item

    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:repmxx:v:5:y:1999:i:1:p:31-45. 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/repm20 .

    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.