A type-2 fuzzy rule-based expert system model for stock price analysis

被引：128
|
作者：
Zarandi, M. H. Fazel [1 ]
Rezaee, B. [1 ]
Turksen, I. B. [2 ]
Neshat, E. [1 ]
机构：
[1] Amirkabir Univ Technol, Polytech Tehran, Dept Ind Engn, Tehran, Iran
[2] Univ Toronto, Dept Mech & Ind Engn, Toronto, ON M5S2 H8, Canada
来源：
EXPERT SYSTEMS WITH APPLICATIONS | 2009年 / 36卷 / 01期
关键词：
Type-2 fuzzy modeling; Fuzzy rule based systems; Forecasting; Stock market; CLUSTER-VALIDITY; LOGIC SYSTEMS; INDEX; SETS;
D O I：
10.1016/j.eswa.2007.09.034
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 type-2 fuzzy rule based expert system is developed for stock price analysis. Interval type-2 fuzzy logic system permits us to model rule uncertainties and every membership value of an element is interval itself. The proposed type-2 fuzzy model applies the technical and fundamental indexes as the input variables. This model is tested on stock price prediction of an automotive manufactory in Asia. Through the intensive experimental tests, the model has successfully forecasted the price variation for stocks from different sectors. The results are very encouraging and can be implemented in a real-time trading system for stock price prediction during the trading period. (C) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码：139 / 154
页数：16
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