Abstract
This paper provides an alternative formulation of the conditional correlation structure in fitting the multivariate GARCH model. A special case is the multivariate ARCH model with random coefficients. Its coherence structure is derived by the correlations between the random coefficients which play an important role in describing the interested heteroscedastic features. The parameter estimation problem can be solved by maximum likelihood estimation and model selection is via the likelihood ratio test. We consider three real applications: (1) the spot and forward rates of the Deutsche Mark against the US dollars; (2) exchange rates of Deutsche Mark and Japanese Yen against US dollars; (3) the Heng Sang index and SES index. Copyright © 2005 Elsevier B.V. All rights reserved.
| Original language | English |
|---|---|
| Pages (from-to) | 1779-1802 |
| Journal | Computational Statistics and Data Analysis |
| Volume | 51 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Dec 2006 |
Citation
Fong, P. W., Li, W. K., & An, H.-Z. (2006). A simple multivariate ARCH model specified by random coefficients. Computational Statistics and Data Analysis, 51(3), 1779-1802. doi: 10.1016/j.csda.2005.11.019Keywords
- Likelihood ratio test
- Maximum likelihood estimation
- Multivariate autoregressive conditional heteroscedasticity
- Nonconstant correlation
- Random coefficient model
- Hadamard product
- Star product