- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
The fluctuations of crude oil prices affect the economic growth of importing and exporting countries as well as regional security and stability. The intrinsic complex features of oil prices and the uncertainty in economic policy pose challenge on the accurate forecasting of crude oil prices. This paper employs independent component analysis (ICA) to analyze crude oil prices which are decomposed into several independent components corresponding to different types of influential factors affecting oil price. We also propose a novel ICA-based support vector regression scheme, namely ICA-SVR2 , for forecasting crude oil prices. The ICA-SVR2 starts from the use of ICA to decompose oil price series into three independent components, which are respectively forecasted by SVR models. The forecasted independent components are then integrated together by developing a new SVR model with independent components as inputs for forecasting crude oil prices. Our experimental results show the usefulness of ICA in identifying the driving factors behind the fluctuations of crude oil prices. A comparative study between ICA-SVR2 and other two models shows that ICA-SVR2 is an effective tool in forecasting crude oil prices.
This paper proposes to use ICA to analyze crude oil prices and develops an ICA-based SVR (ICA-SVR2 ) scheme for forecasting crude oil prices. ICA is helpful to identify the hidden factors behind the fluctuations of international crude oil prices. The proposed ICA-SVR2 model starts from the use of ICA to decompose four international oil price series into three independent components. Then we build three SVR models to forecast the three independent components, respectively. Based on the three independent components as well as the WTI crude oil price series, we construct one integrated SVR model to forecast crude oil prices. Our experimental results show that the integration of ICA with SVR can improve the forecasting accuracy of SVR significantly. Another advantage of ICA is that the independent components obtained may shed insights on understanding the driving forces behind crude oil prices.