IDEAS home Printed from
   My bibliography  Save this paper

Optimal International Diversification: Theory and Practice from a Swiss Investor’s Perspective


  • Foort HAMELINK

    (Tilburg University and Lombard Odier & Cie)


This paper reviews some recent developments in the area of optimal international portfolio diversification and investigates important issues for future research. In the latest models proposed in the financial literature that generate optimal holdings over time, both the quantities of risks (measured by the covariances with various risk factors) and the prices of risk(risk premiums) are time varying. The former are generally specified by some ARCH process, whereas the latter are estimated using instruments such as dividend yield or bond premiums. Available methodologies and the choice of the instruments are discusses in general terms,as weel as the feasibility of active managemant with these models. I test a few of them by considering a Swiss investor who holds an internationally diversified portfolio including local stock indices, as well as an exposure to real estate, and wo may hedge some or all of his currency risk. the empirical tests are performed using a very intuitive and powerful non-parametric threshold ARCH specification to model time-varying sources of risk. Risk premiums are estimated using simple and widely available instruments in the form of macroeconomic variables, but also indicators used in technical analysis. Both the in-sample and the out-of-sample results suggest that the proposed nan-parametric approach is powerful and may constitute a valuable tool for international portfolio managers.

Suggested Citation

  • Foort HAMELINK, 2000. "Optimal International Diversification: Theory and Practice from a Swiss Investor’s Perspective," FAME Research Paper Series rp21, International Center for Financial Asset Management and Engineering.
  • Handle: RePEc:fam:rpseri:rp21

    Download full text from publisher

    File URL:
    Download Restriction: no


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

    Cited by:

    1. Jaroslava Hlouskova & Kurt Schmidheiny & Martin Wagner, 2002. "Multistep Predictions from Multivariate ARMA-GARCH: Models and their Value for Portfolio Management," Diskussionsschriften dp0212, Universitaet Bern, Departement Volkswirtschaft.

    More about this item


    Swiss institutional investors; mixed-asset portfolios; conditional asset allocation; hedging currency risk; QTARCH model; international portfolios; foreign exchange forecasting.;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates


    Access and download statistics


    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:fam:rpseri:rp21. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Marilyn Barja). General contact details of provider: .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.