IDEAS home Printed from https://ideas.repec.org/a/cai/recosp/reco_583_0599.html
   My bibliography  Save this article

Un test de validité de la Value at Risk

Author

Listed:
  • Christophe Hurlin
  • Sessi Tokpavi

Abstract

This paper proposes a new simple test of market risk models validation or Value at Risk (VaR) accuracy. The test exploits the idea that the sequence of VaR violations verifies the properties of a white noise. More precisely, we use the Multivariate Portmanteau statistic of Hosking [1980] to jointly test the absence of autocorrelation in the vector of violation sequences for various coverage rates considered as relevant for the management of risks. We show that this multivariate dimension appreciably improves the power properties of the VaR validation test for reasonable sample sizes. Classification JEL : C23, C11

Suggested Citation

  • Christophe Hurlin & Sessi Tokpavi, 2007. "Un test de validité de la Value at Risk," Revue économique, Presses de Sciences-Po, vol. 58(3), pages 599-608.
  • Handle: RePEc:cai:recosp:reco_583_0599
    as

    Download full text from publisher

    File URL: http://www.cairn.info/load_pdf.php?ID_ARTICLE=RECO_583_0599
    Download Restriction: free

    File URL: http://www.cairn.info/revue-economique-2007-3-page-599.htm
    Download Restriction: free

    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. Elena-Ivona Dumitrescu & Christophe Hurlin & Vinson Pham, 2012. "Backtesting Value-at-Risk: From Dynamic Quantile to Dynamic Binary Tests," Finance, Presses universitaires de Grenoble, vol. 33(1), pages 79-112.
    2. Elena-Ivona DUMITRESCU, 2011. "Backesting Value-at-Risk: From DQ (Dynamic Quantile) to DB (Dynamic Binary) Tests," LEO Working Papers / DR LEO 262, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.

    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

    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:cai:recosp:reco_583_0599. 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: (Jean-Baptiste de Vathaire). General contact details of provider: http://www.cairn.info/revue-economique.htm .

    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.