Backtesting value-at-risk: A GMM duration-based test

B. Candelon, G. Colletaz, C. Hurlin*, S. Tokpavi

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


This paper proposes a new duration-based backtesting procedure for value-at-risk (VaR) forecasts. The GMM test framework proposed by Bontemps (2006) to test for the distributional assumption (i.e., the geometric distribution) is applied to the case of the VaR forecasts validity. Using simple J-statistic based on the moments defined by the orthonormal polynomials associated with the geometric distribution, this new approach tackles most of the drawbacks usually associated to duration-based backtesting procedures. An empirical application for Nasdaq returns confirms that using GMM test leads to major consequences for the expost evaluation of the risk by regulation authorities. JEL: C22, C52, G28.

Original languageEnglish
Pages (from-to)314-343
Number of pages29
JournalJournal of Financial Econometrics
Issue number2
Publication statusPublished - 1 Jan 2011


  • backtesting
  • duration-based test
  • estimation risk
  • GMM
  • value at risk


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