International Crude Oil Price Forecasting based on a Hybrid Model

Due to the serious fluctuations of international crude oil price, to accurately forecast crude oil price is very challenging. Therefore,a hybrid model based on variational mode decomposition(VMD),seasonal autoregressive integrated moving average (SARIMA)and least squares support vector machine(LSSVM)optimized by fruit fly optimization algorithm(FOA)was proposed. First, the international crude oil price series was decomposed into some mode components by VMD. Then,the SARIMA and LSSVM-FOA were established for periodic and nonlinear components, respectively. Finally, the summation of the forecast values of each component was used as the final forecasting result. Empirical results show that the proposed hybrid model can significantly improve the forecasting accuracy of international crude oil price compared with other models.