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 largerdimensional systems, where a full likelihood optimization is often infeasible. The eï¬~@ectiveness of the method is investigated using Monte Carlo simulations as well as a number of empirical applications.
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Paper provided by Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance in its series CeNDEF Working Papers with number
06-13.
Length: Date of creation: 2006 Date of revision: Handle: RePEc:ams:ndfwpp:06-13
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References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
BAUWENS, Luc & LAURENT, SŽbastien & ROMBOUTS, Jeroen, 2003.
"Multivariate GARCH models: a survey,"
CORE Discussion Papers
2003031, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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