IDEAS home Printed from https://ideas.repec.org/a/taf/quantf/v22y2022i6p1193-1216.html
   My bibliography  Save this article

International portfolio choice under multi-factor stochastic volatility

Author

Listed:
  • Marcos Escobar-Anel
  • Sebastian Ferrando
  • Christoph Gschnaidtner
  • Alexey Rubtsov

Abstract

In this article, we develop an identifiable multi-factor stochastic volatility model for international portfolio choice problems in complete and incomplete markets. Allowing for stochastic covariance between financial asset returns and foreign exchange rates, optimal investment strategies are derived in closed form and welfare losses arising from suboptimal investment strategies are analysed. Moreover, we provide a two-step procedure for estimating as well as calibrating the model parameters and use this ansatz to illustrate optimal investment decisions for the S&P 500, the German blue chip index DAX, and the USD/EUR foreign exchange rate. We find, both theoretically and empirically, that the model satisfies various well-known stylized facts of equity and foreign exchange rate markets and that investors who invest myopically or ignore derivative assets can incur substantial welfare losses implying strong evidence for significant welfare benefits from international diversification across different asset classes.

Suggested Citation

  • Marcos Escobar-Anel & Sebastian Ferrando & Christoph Gschnaidtner & Alexey Rubtsov, 2022. "International portfolio choice under multi-factor stochastic volatility," Quantitative Finance, Taylor & Francis Journals, vol. 22(6), pages 1193-1216, June.
  • Handle: RePEc:taf:quantf:v:22:y:2022:i:6:p:1193-1216
    DOI: 10.1080/14697688.2021.2019820
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/14697688.2021.2019820
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/14697688.2021.2019820?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:quantf:v:22:y:2022:i:6:p:1193-1216. 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/RQUF20 .

    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.