Simple exponential smoothing is widely used in forecasting economic time series. This is because it is quick to compute and it generally delivers accurate forecasts. On the other hand, its multivariate version has received little attention due to the complications arising with the estimation....

We provide a feasible generalized least squares estimator for (unrestricted) multivariate GARCH(1, 1) models. We show that the estimator is consistent and asymptotically normally distributed under mild assumptions. Unlike the (quasi) maximum likelihood method, the feasible GLS is considerably...

Exponential smoothing models represent an important prediction tool both in business and in macroeconomics. This paper provides the analytical forecasting properties of the random coefficient exponential smoothing model in the “multiple source of error” framework. The random coefficient...

This paper focuses on the contemporaneous aggregation of GARCH processes. It reconsiders and extends the results achieved by Nijman and Sentana (1996) by showing that the parameters of the weak aggregate GARCH process are exact functions of the underlying processes. More specifically, an...

In this paper we propose a unified framework to analyse contemporaneous and temporal aggregation of a widely employed class of integrated moving average (IMA) models. We obtain a closed-form representation for the parameters of the contemporaneously and temporally aggregated process as a...

This paper focuses on the core inflation measurement in Italy using univariate (national-level inflation) vs. multivariate (city-level inflation) models during the period 1970–2006. We derive algebraic expressions that allow comparison between the reduced form parameters of univariate and...