Crude oil price forecasting: a biogeography-based optimization approach

ABSTRACT

The importance of crude oil in the world economy has made it imperative for efficient models to be designed for predicting future prices. This paper proposes an alternative approach based on a time series and biogeography-based optimization (BMMR–BBO) for the estimation of the West Texas Intermediate (WTI) crude oil price. To evaluate the forecasting ability of the presented model, we compared its performance with those of time series functions. The results of the experiment showed that BMMR-BBO performed better than the other methods and is a fairly good option for crude oil price prediction. The proposed model can be useful in the formulation of policies related to international crude oil price estimations, development plans, and industrial production.

KEYWORDS:

• Biogeography-based optimization
• prediction
• time series
• WTI crude oil price