Nonparametric tests for conditional symmetry in dynamic models

By Miguel A. Delgado, Juan-Carlos Escanciano. 2007

50 citations recorded by the source corpus.

This article proposes omnibus tests for conditional symmetry around a parametric function in a dynamic context. Conditional moments may not exist or may depend on the explanatory variables. Test statistics are suitable functionals of the empirical process of residuals and explanatory variables, whose limiting distribution under the null is nonpivotal. The tests are implemented with the assistance of a bootstrap method, which is justified assuming very mild regularity conditions on the specification of the center of symmetry and the underlying serial dependence structure. Finite sample properties are examined by means of a Monte Carlo experiment.

Subfields: Economics and Econometrics, Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/4dd1915d81c1ca8078c321a0aac83aa51a9b77c8

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In Finance

In Statistics and Probability

Citations in the corpus

Backtesting Parametric Value-at-Risk With Estimation Risk (2010, methodology): “The proof of Theorem 1 is based on applications of the modern theory of empirical processes under martingale conditions, see Delgado and Escanciano (2006) and references therein.”
Specification Tests of Parametric Dynamic Conditional Quantiles (2010, unknown): “Proof of Theorem A1: Theorem A1 in Delgado and Escanciano (2007).”