Crude oil price forecasting using fuzzy time series

Predicting oil price movements is very important for investors. Fuzzy time series which combine people's subjective attitude and objective history values can help people to solve forecasting problems. It has been applied to many areas such as stock index, university enrollments, exchange rates and tourism forecasting. This paper brings fuzzy time series into short term crude oil price forecasting. We use West Taxes Intermediate oil as an example. To evaluate our method's performances, we use root mean square error method. Experiments show that fuzzy time series can produce good forecast results.