Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5096439 | Journal of Econometrics | 2012 | 18 Pages |
Abstract
The paper considers a volatility model which introduces a persistent, integrated or near-integrated, covariate to the standard GARCH(1, 1) model. For such a model, we derive the asymptotic theory of the quasi-maximum likelihood estimator. In particular, we establish consistency and obtain limit distribution. The limit distribution is generally non-Gaussian and represented as a functional of Brownian motions. However, it becomes Gaussian if the covariate has innovation uncorrelated with the squared innovation of the model or the volatility function is linear in parameter. We provide a simulation study to demonstrate the relevance and usefulness of our asymptotic theory.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Heejoon Han, Joon Y. Park,