Testing interval forecasts: a GMM-based approach

Elena Ivona Dumitrescu, Christophe Hurlin and Jaouad Madkour
Additional contact information
Jaouad Madkour: LEO - Laboratoire d'économie d'Orleans [2008-2011] - UO - Université d'Orléans - CNRS - Centre National de la Recherche Scientifique

Working Papers from HAL

Abstract: 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.

Keywords: GMM; Interval forecasts; High Density Region; GMM. (search for similar items in EconPapers)
Date: 2011-08
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-for
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00618467
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://shs.hal.science/halshs-00618467/document (application/pdf)

Related works:
Working Paper: Testing Interval Forecasts: a GMM-Based Approach (2013)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:wpaper:halshs-00618467

Access Statistics for this paper

More papers in Working Papers from HAL
Bibliographic data for series maintained by CCSD ().