Moment-based tests under parameter uncertainty

Christian Bontemps

No 18-883, IDEI Working Papers from Institut d'Économie Industrielle (IDEI), Toulouse

Abstract: This paper considers moment-based tests applied to estimated quantities. We propose a general class of transforms of moments to handle the parameter uncertainty problem. The construction requires only a linear correction that can be implemented in-sample and remains valid for some extended families of non-smooth moments. We reemphasize the attractiveness of working with robust moments, which lead to testing procedures that do not depend on the estimator. Furthermore, no correction is needed when considering the implied test statistic in the out-of-sample case. We apply our methodology to various examples with an emphasis on the backtesting of value-at-risk forecasts.

Keywords: moment-based tests; parameter uncertainty; out-of-sample; discrete distributions; value-at-risk; backtesting (search for similar items in EconPapers)
JEL-codes: C12 (search for similar items in EconPapers)
Date: 2018-03
New Economics Papers: this item is included in nep-ecm and nep-ore
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Related works:
Journal Article: Moment-Based Tests under Parameter Uncertainty (2019)
Working Paper: Moment-Based Tests under Parameter Uncertainty (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:ide:wpaper:32565

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