Working paper
Moment-based tests under parameter uncertainty
Christian Bontemps
n. 18-883, March 2018
Reference
Christian Bontemps, “Moment-based tests under parameter uncertainty”, IDEI Working Paper, n. 18-883, March 2018.
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;
JEL codes
- C12: Hypothesis Testing: General
Research partnership
Scor Chair (centre sustainable)