Extended mean–variance model for reliable evolutionary portfolio optimization

Article type: Research Article

Authors: García, Sandra | Quintana, David^; | Galván, Inés M. | Isasi, Pedro

Affiliations: Department of Computer Science, Universidad Carlos III de Madrid, Leganés, Spain. E-mails: {sgrodrig, dquintan, igalvan}@inf.uc3m.es, isasi@ia.uc3m.es

Note: [] Corresponding author: David Quintana, Department of Computer Science, Universidad Carlos III de Madrid, Av. de la Universidad, 30 Leganés, 28910, Spain. E-mail: dquintan@inf.uc3m.es

Abstract: Real world optimization of financial portfolios pose a challenging multiobjective problem that can be tackled using Evolutionary Algorithms. The fact that the optimization process is subject to the presence of uncertainty concerning asset returns is likely to lead to unreliable solutions. This work suggests extending the classic mean–variance optimization problem with a third explicit robustness objective. This results on sets of portfolios that can be subsequently grouped together according to their reliability. This additional information allows for a better informed decision making regarding asset allocation.

Keywords: Multiobjective evolutionary algorithms, financial portfolio optimization, robustness

DOI: 10.3233/AIC-140600

Journal: AI Communications, vol. 27, no. 3, pp. 315-324, 2014