A TSK type fuzzy rule based system for stock price prediction

被引：195

作者：

Chang, Pei-Chann

Liu, Chen-Hao

机构：

[1] Yuan Ze Univ, Dept Informat Management, Chungli 32026, Taiwan

[2] Yuan Ze Univ, Dept Ind Engn & Management, Chungli 32026, Taiwan

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2008年 / 34卷 / 01期

关键词：

fuzzy rule based systems; forecasting; stock market; step regression analysis; forecasting accuracy;

D O I：

10.1016/j.eswa.2006.08.020

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a Takagi-Sugeno-Kang (TSK) type Fuzzy Rule Based System is developed for stock price prediction. The TSK fuzzy model applies the technical index as the input variables and the consequent part is a linear combination of the input variables. The fuzzy rule based model is tested on the Taiwan Electronic Shares from the Taiwan Stock Exchange (TSE). Through the intensive experimental tests, the model has successfully forecasted the price variation for stocks from different sectors with accuracy close to 97.6% in TSE index and 98.08% in MediaTek. The results are very encouraging and can be implemented in a real-time trading system for stock price prediction during the trading period. (c) 2006 Elsevier Ltd. Ali rights reserved.

引用

页码：135 / 144

页数：10

共 24 条

[1]

Abraham A., 2003, Neural, Parallel & Scientific Computations, V11, P143

[2]

Abraham A, 2001, LECT NOTES COMPUT SC, V2074, P337

[3] Forecasting market trends with neural networks [J].