Application of improving fuzzy time series to predict TAIFEX

Author

Zhao, Liang

Author_Institution

Coll. of Electr. Eng., Henan Univ. of Technol., Zhengzhou, China

fYear

2010

fDate

25-27 Aug. 2010

Firstpage

173

Lastpage

178

Abstract

Taiwan Futures Exchange (TAIFEX) is the world´s 23rd futures exchange to trade SSFs, which is also the 21st financial product offered by the exchange. In this paper, the TAIFEX is predicted based on improving fuzzy time series model. Nature-ratio lengths of intervals technique is employed to partition the universal of discourse of linguistic variable and an improving high-order heuristic function is also used to select the defuzzified value of fuzzified prediction variable to improve prediction accuracy. The experiment result shows that our proposing model has higher prediction accuracy than those of some conventional prediction methods.

Keywords

economic forecasting; fuzzy set theory; heuristic programming; stock markets; time series; SSF trade; TAIFEX prediction; Taiwan future exchange; financial product; fuzzifled prediction variable; fuzzy time series; heuristic function; intervals technique; linguistic variable; nature ratio length; Accuracy; Forecasting; Indexes; Pragmatics; Predictive models; Stock markets; Time series analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Computational Intelligence (IWACI), 2010 Third International Workshop on

Conference_Location

Suzhou, Jiangsu

Print_ISBN

978-1-4244-6334-3

Type

conf

DOI

10.1109/IWACI.2010.5585178

Filename

5585178