Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1157054 | Stochastic Processes and their Applications | 2007 | 20 Pages |
Abstract
The asymptotic distribution of the quasi-maximum likelihood (QML) estimator is established for generalized autoregressive conditional heteroskedastic (GARCH) processes, when the true parameter may have zero coefficients. This asymptotic distribution is the projection of a normal vector distribution onto a convex cone. The results are derived under mild conditions. For an important subclass of models, no moment condition is imposed on the GARCH process. The main practical implication of these results concerns the estimation of overidentified GARCH models.
Related Topics
Physical Sciences and Engineering
Mathematics
Mathematics (General)
Authors
Christian Francq, Jean-Michel Zakoian,