DocumentCode :
2873314
Title :
Fuzzy modeling in stock-market analysis
Author :
Setnes, M. ; van Drempt, O.J.H.
Author_Institution :
Fac. of Inf. Technol. & Syst., Delft Univ. of Technol., Netherlands
fYear :
1999
fDate :
1999
Firstpage :
250
Lastpage :
258
Abstract :
The article examines the application of Takagi-Sugeno fuzzy models (T. Takagi and M. Sugeno, 1985) to the problem of stock market analysis. Different model structures are evaluated in a case study on the modeling of the Dutch AEX-price index. A scenario model is used for examining “what-if” scenarios and a prediction model searches for predictive components in relevant (macro) economic variables. It is found that TS models can be applied successfully in these areas, due to their capability of approximating general nonlinear systems and to their transparency. Further research is recommended
Keywords :
economic cybernetics; fuzzy set theory; modelling; stock markets; uncertainty handling; Dutch AEX-price index; TS models; Takagi-Sugeno fuzzy models; case study; fuzzy modeling; general nonlinear systems; macro economic variables; model structures; prediction model; predictive components; scenario model; stock market analysis; what-if scenarios; Economic forecasting; Environmental economics; Finance; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Linear regression; Neural networks; Predictive models; Takagi-Sugeno model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence for Financial Engineering, 1999. (CIFEr) Proceedings of the IEEE/IAFE 1999 Conference on
Conference_Location :
New York, NY
Print_ISBN :
0-7803-5663-2
Type :
conf
DOI :
10.1109/CIFER.1999.771124
Filename :
771124
Link To Document :
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