We compare the forecasting performances of the classical and the Minnesota-type Bayesian vector autoregressive (VAR … algorithm for variable selection, estimated using Markov Chain Monte Carlo methods. In this regard, we analyze the forecasting … the linear fixed coefficients classical VAR. However, we do not observe marked gains in forecasting power across the …

Traditionally, the literature on forecasting exchange rates with many potential predictors have primarily only … forecasting horizons. …

This paper evaluates the performance of 11 vector autoregressive models in forecasting 15 macroeconomic variables for …

’s financial stress index appear to be strong at almost all horizons and sub-periods. However, the forecasting prowess of the …

as nonparametric and semiparametric models in forecasting the nominal interest rate setting that describes the South …:01 to 2004:12, we compare the out-of-sample forecasting ability of the models over the period 2005:01 to 2008:12. Our …

interest about forecasting such imminent threats for economic stability. In this paper we propose a novel hybrid forecasting … Vector Regression (SVR) methodology that originates from machine learning. We test the forecasting ability of the proposed …-of-sample forecasting. Finally, we argue that this new methodology can be used as an early warning system for forecasting sudden house …

(Gaussian, Lasso-LARS, Lasso-Landweber) in forecasting the U.S. real house price growth. We also compare results with forecasts …-suited model for forecasting the U.S. real house price. Among the least square models, the individual regression with house price …

the random walk model, suggests that the forecasting performance of the monetary model is superior. …