In a typical tactical asset allocation setup, managers generally make their choices with the aim of beating a benchmark portfolio. In this context, the pure Markowitz (1959) strategy does not take two aspects into account: asset returns often show changes in volatility and managers' decisions depend on private information. This paper provides an empirical model for large-scale tactical asset allocation with multivariate GARCH estimates, given a tracking error constraint. Moreover, the Black and Litterman (1991) approach makes it possible to tactically manage the selected portfolio by combining information taken from the time-varying volatility model with some personal 'views' about asset returns.