Wake me up before you GO-GARCH

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 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.