The present paper presents three different short-term oil models on a weekly basis. With these models we try to forecast oil prices out-of-sample up to three months. Two of the models are based on the VAR methodology and consider fundamental factors like the net long position and oil...

The present paper presents three different short-term oil models on a weekly basis. With these models we try to forecast oil prices out-of-sample up to three months. Two of the models are based on the VAR methodology and consider fundamental factors like the net long position and oil...

This paper sheds light on the questions whether it is possible to generate an accurate forecast of the real price of oil and how it can be improved using forecast combinations. For this reason, my work will investigate the out-of-sample performance of thirteen individual forecasting models. The...

We analyse the importance of macroeconomic information, such as industrial production index and oil price, for forecasting daily electricity prices in two of the main European markets, Germany and Italy. We do that by means of mixed-frequency models, introducing a Bayesian approach to reverse...

We study the out-of-sample predictability of the real price of crude oil using forecast combinations constructed from several individual predictors. We find that forecasts of themonthly average price of oil are more accurate than the no-change forecast at horizons ranging from 1 to 24 months...

Most papers in the portfolio choice literature have examined linear predictability frameworks based on the idea that simple but flexible Vector Autoregressive (VAR) models can be expanded to produce portfolio allocations that hedge against the bull and bear dynamics typical of financial markets...

For the timely detection of business-cycle turning points we suggest to use mediumsized linear systems (subset VARs with automated zero restrictions) to forecast the relevant underlying variables, and to derive the probability of the turning point from the forecast density as the probability...

We explore whether modelling parameter time variation improves the point, interval and density forecasts of nine major exchange rates vis-a-vis the US dollar over the period 1976-2015. We find that modelling parameter time variation is needed for an accurate calibration of forecast confidence...