Econometric modelling for short‐term oil price forecasting

There is a lot of interest in forecasting oil price and in analysing which variables most affect price movements, especially whether non‐fundamental variables such as financial activity have any systematic impact on oil price. In this paper we approach both questions by constructing a congruent econometric model with financial and fundamental variables and by analysing the relative weight of the variables in explaining the oil price forecast. After testing for different variables we find that the most accurate forecast from a monthly econometric vector model on oil price is obtained when non‐commercial long positions, petroleum stocks and spare capacity are included as explanatory variables. The incorporation of non‐commercial long positions clearly improves the accuracy of the prediction. The vector model is specified to include empirical cointegration relationship, which provides an approximation on the long‐run restriction postulated by economic theory.