(2000) is applied but generalised to account for weekly periodicities and time-varying volatility. Eventually we find a …

volatility predictor, the results of an application to tactical asset allocation are presented. …

. Issues of parametrization and estimation are discussed. Conditions for covariance stationarity and the existence of the …

accounting for volatility regimes from both a statistical and economic perspective, including out-of-sample portfolio selection …

Das in Finanzmarktdaten zu beobachtende volatility-clustering impliziert, daß große Renditeschocks bei der Preisbildung …The volatility clustering observed in financial market data implies that large net yield shocks increase the … probability of a higher future volatility during the price formation. Starting from the ARCH models which were suggested by Engle …

most important factor in reducing portfolio variance is the use of a flexible model for time varying volatility, rather … good on the present set of measures as the stochastic volatility models, with or without dynamic correlation. …

the common and the idiosyncratic part of each series; it also provides a first identification and estimation of the … more precise estimation of the static and dynamic factors' in-sample levels and covariances in order to achieve better … forecasts. Simulation results on different panels with large time and cross sections are presented. Finally, we carry out an …