of allowing for time variation in vector autoregressive (VAR) model parameters and of constructing forecast combinations …

the mean squared prediction errors of the no-change forecast constructed from average monthly or quarterly data by up to … on monthly closing prices dominates the conventional no-change forecast in terms of forecast accuracy. Although model …-based forecasts also improve when models are estimated using closing prices, only the futures-based forecast significantly outperforms …

discusses how to forecast future oil price movements based on information from both the oil futures market and the spot market …

suggest that oil futures prices have marginal predictive power for the price of oil at a 1-month forecast horizon. However …, they generally lose their forecasting power at higher forecast horizons. The results also suggest that exchange rates help … predicting oil prices at higher forecast horizons. The paper also considers forecast averaging and variable selection methods …

produce accurate forecast based on a description of history patterns in crude oil prices …

This paper explores a range of different forecast methods for Brent oil prices and analyses their performance relative … across forecast horizons. To address this instability, we propose a forecast combination for predicting quarterly real Brent … generates forecasts whose performance is robust over time. The improvements in forecast accuracy and stability are noticeable in …

-time forecasts of the real price of oil can be more accurate than the no-change forecast at horizons up to one year. In some cases … prices, forecasts based on AR and ARMA models, and the no-change forecast. In addition, these VAR models have consistently … forecasters to interpret their oil price forecast in light of economic models and to evaluate its sensitivity to alternative …