difficult to beat in forecasting competitions. In some sense, by using our approach to predictive factor proxy selection, one is …

macroeconomic indicators (not including spreads) perform best when forecasting inflation in non-volatile time periods, while …

Models based on economic theory have serious problems at forecasting exchange rates better than simple univariate … this paper, we propose to forecast exchange rates with a large Bayesian VAR (BVAR), using a panel of 33 exchange rates vis … forecasting. In addition, we adopt a driftless random walk prior, so that cross-dynamics matter for forecasting only if there is …

forecasting model for another variable, and hence our use of terminology such as ?out-of-sample Granger causality? (see e …

forecast complexity. We aim to identify model elements which are crucial for the valuation of project finance in practice … analyze their impact on the valuation result. For forecast complexity, we apply different volatility and correlation … forecasting techniques, e.g. correlation forecasts based on historical values and on a dynamic conditional correlation (DCC) model …

The paper addresses the issue of forecasting a large set of variables using multivariate models. In particular, we … propose three alternative reduced rank forecasting models and compare their predictive performance with the most promising … forecast, and for key variables such as industrial production growth, inflation, and the federal funds rate. …