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

Authors:
M. H. Fazel Zarandi;B. Rezaee;I. B. Turksen;E. Neshat
Affiliations:
Department of Industrial Engineering, Amirkabir University of Technology (Polytechnic of Tehran), P.O. Box 15875-4413, Tehran, Iran;Department of Industrial Engineering, Amirkabir University of Technology (Polytechnic of Tehran), P.O. Box 15875-4413, Tehran, Iran;Department of Mechanical and Industrial Engineering, University of Toronto, 5 King College Road, Toronto, ON, Canada M5S2H8;Department of Industrial Engineering, Amirkabir University of Technology (Polytechnic of Tehran), P.O. Box 15875-4413, Tehran, Iran
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

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Abstract

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.