Journal
FUZZY SETS AND SYSTEMS
Volume 188, Issue 1, Pages 16-26Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.fss.2011.05.013
Keywords
Fuzzy numbers; Genetic algorithms; Multiple criteria evaluation; Portfolio selection; Finance
Funding
- Ministerio de Educacion y Ciencia of Spain [MTM2008-03993]
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This paper presents a new procedure that extends genetic algorithms from their traditional domain of optimization to fuzzy ranking strategy for selecting efficient portfolios of restricted cardinality. The uncertainty of the returns on a given portfolio is modeled using fuzzy quantities and a downside risk function is used to describe the investor's aversion to risk. The fitness functions are based both on the value and the ambiguity of the trapezoidal fuzzy number which represents the uncertainty on the return. The soft-computing approach allows us to consider uncertainty and vagueness in databases and also to incorporate subjective characteristics into the portfolio selection problem. We use a data set from the Spanish stock market to illustrate the performance of our approach to the portfolio selection problem. (C) 2011 Elsevier B.V. All rights reserved.
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