We frequently observe that one of the aims of time series analysts is to predict future values of the data. For weakly dependent data, when the model is known up to a finite set of parameters, its statistical properties are well documented and exhaustively examined. However, if the model was...

We propose a test for separability of the correlation structure of a multivariate time series. We construct test statistics based on a spectral density matrix estimated in a nonparametric way and derive their asymptotic properties. We use simulation to check the performance in finite samples