This paper considers forecasting the conditional mean and variance from an ARMA model with GARCH in mean effects. Expressions for the optimal predictors and their conditional and unconditional MSE's are presented. We also derive the formula for the covariance structure of the process and its...

The purpose of this paper is to examine the covariance structure of multivariate GARCH (M-GARCH) models that have been introduced in the literature the last fifteen years, and have been greatly favoured by time series analysts and econometricians. In particular, we analyze the second moments of...

This paper extents Karanasos (1999a) results for the n Component GARCH(1,1) and the two Component GARCH(2,2) models and it further examines the n Component GARCH(n,n) model. In particular, we present the GARCH(n^2;n^2) representation of the aggregate variance and we give the condition for the...

The purpose of this paper is to examine the covariance structure of mixed ARMA models, as discussed in Granger and Morris (1976). The method we use to obtain the autocovariances is based on the Wold representation of an ARMA model as it is given in Pandit (1973) or in Karanasos (2000). We give...

This paper explores the interactions between cross-sectional aggregation and persistence of volatility shocks. We derive the ARMA-GARCH representation that linear aggregates of ARMA processes with GARCH errors admit, and establish conditions under which persistence in volatility of the aggregate...