-type models provide poor out-of-sample forecasts of volatility. This is primarily based on the use of traditional forecast … evaluation criteria concerning the accuracy and the unbiasedness of forecasts. In this paper we provide an assessment of … suitable for the evaluation of volatility forecasts. …

The predictive accuracy of various econometrics models, including random walks, vector autoregressive and vector error …

development of adjacent age groups is assured allowing for consistent forecasts. We develop an appropriate Markov Chain Monte … approach we are able to asses uncertainty intuitively by constructing error bands for the forecasts. We observe that in … particular parameter uncertainty is important for long-run forecasts. This implies that hitherto existing forecasting methods …

similar development of adjacent age groups is assured, allowing for consistent forecasts. We develop an appropriate Markov … Bayesian approach we are able to assess uncertainty intuitively by constructing error bands for the forecasts. We observe that … in particular parameter uncertainty is important for long-run forecasts. This implies that existing forecasting methods …

empirical illustration is given for mid-term forecasts simultaneously made by two broker-dealers for several countries. …

Using density forecasts, we compare the predictive performance of dur ation models that have been developed fo …

the least reliable, whereas real GDP and real private consumption data are the most reliable. In addition, early forecasts … forecasts of all the variables seem to be no more accurate than naïve forecasts based on the historical mean of the final data. …