components and modeling and forecasting them separately instead of directly forecasting the realized volatility is shown to lead …

forecasting performance of the new model is found to be, in general, superior to that of the set of volatility models recently …

period 1970Q1 - 2003Q4 for ten macroeconomic variables. The years 2000 - 2003 are used as forecasting period. A range of … different univariate forecasting methods is applied. Some of them are based on linear autoregressive models and we also use some … forecasting variables which need considerable adjustments in their levels when joining German and EMU data. These results suggest …

forecasting the quarterly growth rate of Euro area GDP and its components, using a very large set of monthly indicators taken from …

We propose a new approach to forecasting the term structure of interest rates, which allows to efficiently extract the … forecasting performance of our proposed model relative to most of the existing alternative speci.cations. While most of the … and useful for forecasting. …

The adoption of inflation targeting in emerging market economies makesaccurate forecasting of inflation and output …, autoregressive and small-scale vector autoregressive models can be suggested as forecasting tools. However,these models include only … forecasting performance of the models considered depends on the statistical properties of the series to be forecast, which are …

Models based on economic theory have serious problems at forecasting exchange rates better than simple univariate … forecasting. In addition, we adopt a driftless random walk prior, so that cross-dynamics matter for forecasting only if there is …