Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1146045 | Journal of Multivariate Analysis | 2011 | 10 Pages |
Abstract
The asymptotic properties of the quasi-maximum likelihood estimator (QMLE) of vector autoregressive moving-average (VARMA) models are derived under the assumption that the errors are uncorrelated but not necessarily independent nor martingale differences. Relaxing the martingale difference assumption on the errors considerably extends the range of application of the VARMA models, and allows one to cover linear representations of general nonlinear processes. Conditions are given for the asymptotic normality of the QMLE. Particular attention is given to the estimation of the asymptotic variance matrix, which may be very different from that obtained in the standard framework.
Related Topics
Physical Sciences and Engineering
Mathematics
Numerical Analysis
Authors
Y. Boubacar Mainassara, C. Francq,