I would like to thank the anonymous referee for making useful comments to improve this paper.
ROBUST ESTIMATION FOR THE ORTHOGONAL GARCH MODEL *
Article first published online: 29 AUG 2012
© 2012 The Author. The Manchester School © 2012 John Wiley & Sons Ltd and The University of Manchester
The Manchester School
Volume 81, Issue 6, pages 904–924, December 2013
How to Cite
IQBAL, F. (2013), ROBUST ESTIMATION FOR THE ORTHOGONAL GARCH MODEL . The Manchester School, 81: 904–924. doi: 10.1111/j.1467-9957.2012.02315.x
Manuscript received 15.12.11; final version received 22.4.12.
- Issue published online: 8 OCT 2013
- Article first published online: 29 AUG 2012
In this paper, we propose a class of robust M-estimators for the orthogonal generalized autoregressive conditional heteroscedastic (GARCH) model. The method involves the estimation of only univariate GARCH models and hence easy to estimate and does not put additional constraints on the model. The forecasting performance of the class of robust estimators in predicting correlation and value-at-risk using various evaluation measures are investigated. We found empirical evidences of the better predictive potential of estimators such as least absolute deviation and B-estimator over the widely used quasi-maximum likelihood estimator when the error distribution is heavy-tailed and asymmetric. Applications to real data sets are also presented.