6533b85bfe1ef96bd12bbe0d

RESEARCH PRODUCT

Prediction of stock index futures prices based on fuzzy sets and multivariate fuzzy time series

Shan XiongHaifeng GuoYuanjing GeBaiqing SunHamid Reza Karimi

subject

Adaptive neuro fuzzy inference systemComputer scienceCognitive NeuroscienceFuzzy setcomputer.software_genreStock market indexDefuzzificationFuzzy logicComputer Science ApplicationsArtificial IntelligenceFuzzy set operationsRough setData miningFutures contractcomputer

description

Abstract This paper makes a prediction of Chinese stock index (CSI) future prices using fuzzy sets and multivariate fuzzy time series method. We select Chinese CSI 300 index futures as the research object. The fuzzy time series model combines the fuzzy theory and the time series theory, thus this model can solve the fuzzy data in stock index futures prices. This paper establishes a multivariate model and improves the accuracy of computation. By combing traditional fuzzy time series models and rough set method, we use fuzzy c-mean algorithm to make the data into discrete. Further more, we deal with the rules in mature modules of the rough set and then refine the rules using data mining algorithms. Finally, we use the CSI 300 index futures to test our model and make a prediction of the prices.

yearjournalcountryeditionlanguage
2015-03-01Neurocomputing
https://doi.org/10.1016/j.neucom.2014.09.018