A Type-2 Fuzzy Rule-Based Expert System Model for Portfolio Selection

DOI

10.2991/jcis.2008.116How to use a DOI?

Keywords

interval type-2 fuzzy set, fuzzy c-means clustering, validity index

Abstract

This paper presents a type-2 fuzzy rule based expert system to handle uncertainty in complex problems such as portfolio selection. In a type-2 fuzzy expert system both antecedent and consequent have type-2 membership function. This research uses indirect approach fuzzy modeling, where the rules are extracted automatically by implementing a clustering approach. For this purpose, a new cluster analysis approach based on Fuzzy C-Means (FCM) is developed to generate primary membership of type-2 membership functions. A new cluster validity index based on Xie-Beni validity index is presented. The proposed type-2 fuzzy model is applied in stock market factors (such as risk, return, dividend,…) as the input variables. This model is tested on Tehran Stock Exchange (TSE). Through the intensive experimental tests, the model has successfully selected the most efficient portfolio based on individual investor. The results are very encouraging and can be implemented in a real-time trading system for stock.

Copyright

© 2008, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - M.H. Zarandi
AU  - E. Hajigol Yazdi
PY  - 2008/12
DA  - 2008/12
TI  - A Type-2 Fuzzy Rule-Based Expert System Model for Portfolio Selection
BT  - Proceedings of the 11th Joint Conference on Information Sciences (JCIS 2008)
PB  - Atlantis Press
SP  - 690
EP  - 697
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2008.116
DO  - 10.2991/jcis.2008.116
ID  - Zarandi2008/12
ER  -