Crude Oil Price Forecasting Using Fuzzy Time Series

摘要：

Predicting oil price movements is very important for investors. Fuzzy time series which combine peoples 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 methods performances, we use root mean square error method. Experiments show that fuzzy time series can produce good forecast results.

关键词： Crude oil price forecasting Fuzzy time series Root mean square error

作者: Xiaoxiao Zhang Qizong Wu Jianfeng Zhang

作者单位: School of Management and EconomicsBeijing Institute of Technology Beijing 100081, China Zhengzhou Coal Machine Comprehensive Accessories Co.Ltd Zhengzhou, 450013, Henan Province, China

会议类型: 国际会议

会议名称: 2010 Third International Symposium on Knowledge Acquisition and Modeling(第三届知识获取与建模国际研讨会 KAN 2010)

会议地点: 武汉

会议语种:英文

页码: 213-216

在线出版日期: 2010-10-20（万方平台首次上网日期，不代表论文的发表时间）