Abstract
A test for detecting departures from meta-ellipticity for multivariate stationary time series is proposed. The large sample behavior of the test statistic is shown to depend in a complicated way on the underlying copula as well as on the serial dependence. Valid asymptotic critical values are obtained by a bootstrap device based on subsampling. The finite-sample performance of the test is investigated in a large-scale simulation study, and the theoretical results are illustrated by a case study involving financial log returns.
| Original language | English |
|---|---|
| Pages (from-to) | 121-140 |
| Number of pages | 20 |
| Journal | Dependence Modeling |
| Volume | 9 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1 Jan 2021 |
Keywords
- elliptical copula
- empirical process
- financial log returns
- goodness-of-fit test
- subsampling bootstrap