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