Interval Forecasting of Crude Oil Price

Abstract

Uncertainty is the main obstacle in predicting crude oil price. Although there are various models and computational methods on crude oil price forecasting in literature, most of them do not effectively predict the variability of crude oil price due to uncertainty. Very recently, Hu and He [2] reported of using ILS (Interval Least Square) approach to forecast the stock market and obtained much better results than that obtained with traditional point methods, In this paper, we investigate if the ILS approach can forecast the relationship between commodity inventory levels and crude oil spot prices effectively. Our empirical study suggests that both the ILS method and the confidence interval method can produce comparable quality forecasts. While the computational result produced by the ILS method seems slightly worse than the 95% confidence intervals in two quality measurements, the differences are negligible. On a new forecasting quality measurement proposed in this paper, the ILS method produces results better than the 95% confidence intervals. Hence, interval method is a feasible alternative in crude oil price forecasting.