A comparative study of multi-objective evolutionary algorithms to optimize the selection of investment portfolios with cardinality constraints

Authors:
Feijoo E. Colomine Duran;Carlos Cotta;Antonio J. Fernández-Leiva
Affiliations:
Laboratorio de Computación de Alto Rendimiento (LCAR), Universidad Nacional Experimental del Táchira (UNET), San Cristóbal, Venezuela;Dept. Lenguajes y Ciencias de la Computación, ETSI Informática, University of Málaga, Málaga, Spain;Dept. Lenguajes y Ciencias de la Computación, ETSI Informática, University of Málaga, Málaga, Spain
Venue:
EvoApplications'12 Proceedings of the 2012t European conference on Applications of Evolutionary Computation
Year:
2012

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Abstract

We consider the problem of selecting investment components according to two partially opposed measures: the portfolio performance and its risk. We approach this within Markowitz's model, considering the case of mutual funds market in Europe until July 2010. Comparisons were made on three multi-objective evolutionary algorithms, namely NSGA-II, SPEA2 and IBEA. Two well-known performance measures are considered for this purpose: hypervolume and R2 indicator. The comparative analysis also includes an assessment of the financial efficiency of the investment portfolio selected according to Sharpe's index, which is a measure of performance/risk. The experimental results hint at the superiority of the indicator-based evolutionary algorithm.