Abstract
In this paper we propose finite-sample multivariate tests for ARCH effects in the errors of vector autoregressive (VAR) models using Monte Carlo testing techniques and the bootstrap. The tests under consideration are combined equation-by-equation LM tests, multivariate LM tests and LM tests of constant error covariance matrix. We use a parametric bootstrap to circumvent the problem that the test statistics in VAR models are not free of nuisance parameters under the null hypothesis. The tests are evaluated in simulation experiments and the bootstrap tests are found to have excellent size and power properties. The LM tests of constant error covariance matrix outperform the combined LM tests and multivariate LM tests in terms of power.
Original language | English |
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Title of host publication | Proceedings in Computational Statistics : 2014 |
Number of pages | 8 |
Publisher | Physica-Verlag |
Publication date | 2014 |
Pages | 265-272 |
ISBN (Electronic) | 978-2-8399-1347-8 |
Publication status | Published - 2014 |
MoE publication type | A4 Article in conference proceedings |
Event | International Conference on Computational Statistics - Geneva, Switzerland Duration: 19.08.2014 → 22.08.2014 Conference number: 21 |
Keywords
- 112 Statistics and probability
- Conditional heteroskedasticity
- Vector autoregressive model
- Monte Carlo test
- Bootstrap
- KOTA2014