Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/86322 
Year of Publication: 
2006
Series/Report no.: 
Tinbergen Institute Discussion Paper No. 06-079/4
Publisher: 
Tinbergen Institute, Amsterdam and Rotterdam
Abstract: 
In this paper we present a new three-step approach to the estimation of Generalized Orthogonal GARCH (GO-GARCH) models, as proposed by van der Weide (2002). The approach only requires (non-linear) least-squares methods in combination with univariate GARCH estimation, and as such is computationally attractive, especially in larger-dimensional systems, where a full likelihood optimization is often infeasible. The effectiveness of the method is investigated using Monte Carlo simulations as well as a number of empirical applications.
Subjects: 
Multivariate GARCH
Non-Linear Least-Squares
Maximum Likelihood
JEL: 
C13
C32
Document Type: 
Working Paper

Files in This Item:
File
Size
678.33 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.