-memory counterparts. Since long memory models should have a particular advantage over long forecasting horizons, we consider predictions …

-memory counterparts. Since long memory models should have a particular advantage over long forecasting horizons, we consider predictions …

For forecasting volatility of futures returns, the paper proposes an indirect method based on the relationship between … futures and the underlying asset for the returns and time-varying volatility. For volatility forecasting, the paper considers … that the new method based on stochastic volatility models with the asymmetry and long memory outperforms the forecasting …

variancefunctions. In a genuine out-of-sample forecasting experiment theperformance of the best fitted asMA-asQGARCH model is compared … topure asMA and no-change forecasts. This is done both in terms ofconditional mean forecasting as well as in terms of risk … forecasting. …

of point and density forecasting. The relative accuracy is higher when the full distribution is predicted. We also …

forecasting volatility model with the most appropriate error distribution. The results suggest the presence of leverage effect … forecasting model that could guarantee a sound policy decisions. …

forecasting volatility. Key papers in this area include Andersen, Bollerslev, Diebold and Labys (2003), Corsi (2004), Andersen …

ability to anticipate the output growth. For this purpose, we propose an extended MIDAS model that allows the forecasting of …