shows the relationship between the asymptotic distributions of the 2sQML estimator for the RBEKK model and variance … targeting quasi-maximum likelihood estimator for the VT-BEKK model. Monte Carlo experiments show that the bias of the 2sQML …

shows the relationship between the asymptotic distributions of the 2sQML estimator for the RBEKK model and variance … targeting quasi-maximum likelihood estimator for the VT-BEKK model. Monte Carlo experiments show that the bias of the 2sQML …

are more precisely estimated when no variance targeting is employed. Bias properties are exacerbated for a heavier … be more pronounced under variance targeting. Some effects further intensify if one uses ML based on a leptokurtic … targeting is used. Thus, if computational costs are not prohibitive, variance targeting should probably be avoided. …

are more precisely estimated when no variance targeting is employed. Bias properties are exacerbated for a heavier … be more pronounced under variance targeting. Some effects further intensify if one uses ML based on a leptokurtic … targeting is used. Thus, if computational costs are not prohibitive, variance targeting should probably be avoided. …

We establish the strong consistency and the asymptotic normality of the variance-targeting estimator (VTE) of the …

and multivariate GARCH models. In terms of variance targeting estimation recent research has pointed out that at least … conditions may not be satisfied in practice for financial returns highlighting a large drawback of variance targeting estimation …. In this paper we consider the large-sample properties of the variance targeting estimator for the multivariate extended …

This paper considers asymptotic inference in the multivariate BEKK model based on (co-)variance targeting (VT). By defi …