IDEAS home Printed from https://ideas.repec.org/a/taf/eurjfi/v13y2007i7p645-655.html
   My bibliography  Save this article

Factor-based, Non-parametric Risk Measurement Framework for Hedge Funds and Fund-of-Funds

Author

Listed:
  • T. R. J. Goodworth
  • C. M. Jones

Abstract

A factor-decomposition based framework is presented that facilitates non-parametric risk analysis for complex hedge fund portfolios in the absence of portfolio level transparency. This approach has been designed specifically for use within the hedge fund-of-funds environment, but is equally relevant to those who seek to construct risk-managed portfolios of hedge funds under less than perfect underlying portfolio transparency. Using dynamic multivariate regression analysis coupled with a qualitative understanding of hedge fund return drivers, one is able to perform a robust factor decomposition to attribute risk within any hedge fund portfolio with an identifiable strategy. Furthermore, through use of Monte Carlo simulation techniques, these factors can be employed to generate implied risk profiles at either the constituent fund or aggregate fund-of-funds level. As well as being pertinent to risk forecasting and monitoring, such methods also have application to style analysis, profit attribution, portfolio stress testing and diversification studies. This paper outlines such a framework and presents sample results in each of these areas.

Suggested Citation

  • T. R. J. Goodworth & C. M. Jones, 2007. "Factor-based, Non-parametric Risk Measurement Framework for Hedge Funds and Fund-of-Funds," The European Journal of Finance, Taylor & Francis Journals, vol. 13(7), pages 645-655.
    • Handle: RePEc:taf:eurjfi:v:13:y:2007:i:7:p:645-655
    DOI: 10.1080/13518470701322284
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/13518470701322284
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/13518470701322284?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.

    Citations

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


    Cited by:

    1. Szabolcs Blazsek & Anna Downarowicz, 2013. "Forecasting hedge fund volatility: a Markov regime-switching approach," The European Journal of Finance, Taylor & Francis Journals, vol. 19(4), pages 243-275, April.

    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:eurjfi:v:13:y:2007:i:7:p:645-655. 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/REJF20 .

    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.