A Study of Value-at-Risk Based on M-Estimators of the Conditional Heteroscedastic Models
Article first published online: 26 FEB 2011
Copyright © 2011 John Wiley & Sons, Ltd.
Journal of Forecasting
Volume 31, Issue 5, pages 377–390, August 2012
How to Cite
Iqbal, F. and Mukherjee, K. (2012), A Study of Value-at-Risk Based on M-Estimators of the Conditional Heteroscedastic Models. J. Forecast., 31: 377–390. doi: 10.1002/for.1224
- Issue published online: 8 JUL 2012
- Article first published online: 26 FEB 2011
- Manuscript Accepted: 29 DEC 2010
- Manuscript Revised: 9 JUL 2010
- Manuscript Received: 11 JAN 2010
- M-tests for financial data
In this paper, we investigate the performance of a class of M-estimators for both symmetric and asymmetric conditional heteroscedastic models in the prediction of value-at-risk. The class of estimators includes the least absolute deviation (LAD), Huber's, Cauchy and B-estimator, as well as the well-known quasi maximum likelihood estimator (QMLE). We use a wide range of summary statistics to compare both the in-sample and out-of-sample VaR estimates of three well-known stock indices. Our empirical study suggests that in general Cauchy, Huber and B-estimator have better performance in predicting one-step-ahead VaR than the commonly used QMLE. Copyright © 2011 John Wiley & Sons, Ltd.