Testing interval forecasts: a GMM-based approach - Archive ouverte HAL
Pré-Publication, Document De Travail Journal of Forecasting Année : 2011

Testing interval forecasts: a GMM-based approach

Résumé

This paper proposes a new evaluation framework for interval forecasts. Our model free test can be used to evaluate intervals forecasts and High Density Regions, potentially discontinuous and/or asymmetric. Using a simple J-statistic, based on the moments de ned by the orthonormal polynomials associated with the Binomial distribution, this new approach presents many advantages. First, its implementation is extremely easy. Second, it allows for a separate test for unconditional coverage, independence and conditional coverage hypotheses. Third, Monte-Carlo simulations show that for realistic sample sizes, our GMM test has good small-sample properties. These results are corroborated by an empirical application on SP500 and Nikkei stock market indexes. It con rms that using this GMM test leads to major consequences for the ex-post evaluation of interval forecasts produced by linear versus nonlinear models.
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Dates et versions

halshs-00618467 , version 1 (15-09-2011)

Identifiants

  • HAL Id : halshs-00618467 , version 1

Citer

Elena-Ivona Dumitrescu, Christophe Hurlin, Jaouad Madkour. Testing interval forecasts: a GMM-based approach. 2011. ⟨halshs-00618467⟩
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