Asymptotic theory for multivariate GARCH processes
We provide in this paper asymptotic theory for the multivariate GARCH(p,q) process. Strong consistency of the quasi-maximum likelihood estimator (MLE) is established by appealing to conditions given by Jeantheau (Econometric Theory 14 (1998), 70) in conjunction with a result given by Boussama (Ergodicity, mixing and estimation in GARCH models, Ph.D. Dissertation, University of Paris 7, 1998) concerning the existence of a stationary and ergodic solution to the multivariate GARCH(p,q) process. We prove asymptotic normality of the quasi-MLE when the initial state is either stationary or fixed.
Year of publication: |
2003
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Authors: | Comte, F. ; Lieberman, O. |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 84.2003, 1, p. 61-84
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Publisher: |
Elsevier |
Keywords: | Asymptotic normality BEKK Consistency GARCH Martingale CLT |
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