In this paper long-run forecasting of multicointegrating variables is investigated. Multicointegration typically occurs …" restriction on out-of-sample valuation and forecasting accuracy of such variables is of interest. In particular, we compare the … long-run forecasting performance of the multicointegrated variables between a model that correctly imposes the "common …

market volatility by macroeconomic and financial variables. We go beyond forecasting stock market volatility (by large the …

This paper applies three universal approximators for forecasting. They are the Artificial Neural Networks, the …

We propose a parametric state space model with accompanying estimation and forecasting framework that combines long … process, the model consistently belongs to the 10% Model Confidence Set when considering out-of-sample forecasting performance … as the only one among four competing dynamic models for all forecasting horizons when applied to high frequency stock …

forecasting problem posed by Stock and Watson (1999), and compute the MCS for their set of inflation forecasts. Second, we compare …

versa occurs over time. Such a change has important implications for forecasting, as negligence may lead to inaccurate model …. Seven different forecasting strategies based on a biasedcorrected estimator are compared by means of a large-scale Monte … predictive ability and its balanced performance among different settings strongly advocate the use of forecasting strategies …