计算机工程与应用Issue(5)：252-256,260,6.DOI:10.3778/j.issn.1002-8331.1204-0466
模糊时间序列建模及股票市场多步预测
Multi-step forecasting of stock markets based on fuzzy time series model
摘要
Abstract
First, the universe of the discourse is divided into subintervals with the midpoints between two adjacent cluster centers generated by the fuzzy clustering method as their endpoints. And the sub-intervals are employed to fuzzify the time series into fuzzy time series. Then, the fuzzy time series model of high-order fuzzy relationships with multiple fac-tors is built according to the main indexes representing stock price and trading volume. Finally, the model built in this paper is used to perform one-and multi-step forecasting of the daily Shanghai Stock Exchange composite index and Shen-zhen Stock Exchange component index, respectively. Comparing with the benchmark model, one-step forecasting results show that the model improves the prediction accuracy and percent correct of the market up&down trend prediction, and multi-step forecasting results show that the model has good generalization.关键词
模糊时间序列/股票市场/多步预测Key words
fuzzy time series/stock market/multi-step forecast分类
数理科学引用本文复制引用
杨一文,蔺玉佩..模糊时间序列建模及股票市场多步预测[J].计算机工程与应用,2014,(5):252-256,260,6.基金项目
国家自然科学基金（No.70471026）；教育部人文社会科学研究基金（No.09YJAZH073）。 （）
