In this paper we propose bootstrapping Hannan and Rissanen (1982) estimators in stationary invertible VARMA models, with known order (p, q). Although we consider bootstrapping such models under the echelon form parameterization, the results we derive herein remain valid to other alternative identification issues. In particular, we shall exploit the theoretical developments stated in Dufour and ...

A useful class of partially nonstationary vector autoregressive moving average (VARMA) models is considered with regard to parameter estimation. An exact maximum likelihood (EML) approach is developed on the basis of a simple transformation applied to the error-correction representation of the models considered. The employed transformation is shown to provide a standard VARMA model with the imp...

We propose a new model for volatility forecasting which combines the Generalized Dynamic Factor Model (GDFM) and the GARCH model. The GDFM, applied to a large number of series, captures the multivariate information and disentangles the common and the idiosyncratic part of each series of returns. In this financial analysis, both these components are modeled as a GARCH. We compare GDFM+GARCH and ...

Strong consistency and asymptotic normality of a Gaussian quasi-maximum likelihood estimator for the parameters causal, invertible, identifiable vector autoregressive-moving average (VARMA) model are established in an indirect way. The proof is based on similar results much wider class VARMA models with time-dependent coefficients, hence context non-stationary heteroscedastic time series. For t...

The autoregressive conditional heteroskedasticity (ARCH) and generalized autoregressive conditional heteroskedasticity (GARCH) models take the dependency of the conditional second moments. The idea behind ARCH/GARCH model is quite intuitive. For ARCH models, past squared innovations describes the present squared volatility. For GARCH models, both squared innovations and the past squared volatil...

This paper builds a structural VARMA (SVARMA) model for investigating Canadian monetary policy. Despite the support for a VARMA model for monetary policy analysis, the traditional VAR and SVAR models have predominantly been used in the literature mainly due to difficulties associated with the identification and estimation of such a model. Using the scalar component model (SCM) proposed by Athan...