Specification testing in nonparametric AR-ARCH models
Statistics Theory
2016-10-12 v1 Statistics Theory
Abstract
In this paper an autoregressive time series model with conditional heteroscedasticity is considered, where both conditional mean and conditional variance function are modeled nonparametrically. A test for the model assumption of independence of innovations from past time series values is suggested. The test is based on an weighted -distance of empirical characteristic functions. The asymptotic distribution under the null hypothesis of independence is derived and consistency against fixed alternatives is shown. A smooth autoregressive residual bootstrap procedure is suggested and its performance is shown in a simulation study.
Cite
@article{arxiv.1610.03215,
title = {Specification testing in nonparametric AR-ARCH models},
author = {Marie Hušková and Natalie Neumeyer and Tobias Niebuhr and Leonie Selk},
journal= {arXiv preprint arXiv:1610.03215},
year = {2016}
}