Characteristic function-based hypothesis tests under weak dependence

Authors:
Anne Leucht
Affiliations:
-
Venue:
Journal of Multivariate Analysis
Year:
2012

Citing 3
Cited 1

Time Series Analysis, Forecasting and Control

Time Series Analysis, Forecasting and Control
Invariant tests for symmetry about an unspecified point based on the empirical characteristic function

Journal of Multivariate Analysis
Simulation of Lévy-driven Ornstein-Uhlenbeck processes with given marginal distribution

Computational Statistics & Data Analysis

Dependent wild bootstrap for degenerate U- and V-statistics

Journal of Multivariate Analysis

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Abstract

In this article we propose two consistent hypothesis tests of L"2-type for weakly dependent observations based on the empirical characteristic function. We consider a symmetry test and a goodness-of-fit test for the marginal distribution of a time series. The asymptotic behaviour under the null as well as fixed and certain local alternatives is investigated. Since the limit distributions of the test statistics depend on unknown parameters in a complicated way, we suggest to apply certain parametric bootstrap methods in order to determine critical values of the tests.