We connect the rate of consistency of the quasi-maximum likelihood estimator in GARCH(p; q) sequences with the number of the moments of the innovations.
A note on the uniqueness of the quasi-likelihood estimator
β Scribed by George Tzavelas
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 219 KB
- Volume
- 38
- Category
- Article
- ISSN
- 0167-7152
No coin nor oath required. For personal study only.
β¦ Synopsis
The existence and the asymptotic performance of the quasi-likelihood estimator was studied by Kagan (1976), McCullagh (1983) and Morton (1981 ). However, their proof do not reveal whether multiple roots may yield one or more consistent solutions. In this paper, arguing as Cramer (1946( ), Huzurbazar (1948) ) we prove that if there is a consistent quasi-likelihood estimator, then it is unique with probability tending to one.
π SIMILAR VOLUMES
In estimating a bounded normal mean, it is known that the maximum likelihood estimator is inadmissible for squared error loss function. In this paper, we discuss the admissibility for other loss functions. We prove that the maximum likelihood estimator is admissible under absolute error loss.