Implications of nonlinearity, nonstationarity and misspecification are considered from a forecasting perspective. My …

This paper explores the forecasting abilities of Markov-Switching models. Although MS models generally display a … models. In order to explain this poor performance, we use a forecasting error decomposition. We identify four components and …

volatility information improves the day volatility estimation. The results indicate a forecasting improvement using bivariate …

-dimensional surfaces. We propose to extend their use to finance and, in particular, to forecasting yield curves. We present the results of … Kriging method based on the anisotropic variogram. Furthermore, a comparison with other recent methods for forecasting yield … competitive with the other forecasting models considered. …

This paper is an exercise in applied macroeconomic forecasting. We examine the forecasting power of a vector error … expenditure as suggested by the economic theory. We compare the estimated forecasting values of the endogenous variables to the …

using these models in an out-of-sample forecasting exercise compared with the forecasts obtained based on the usual linear …

We provide empirical evidence of volatility forecasting in relation to asymmetries present in the dynamics of both … informative than "good" jump risk in forecasting future volatility. The volatility forecasting model proposed is able to capture …