Bi-objective portfolio optimization using a customized hybrid NSGA-II procedure

Authors:
Kalyanmoy Deb;Ralph E. Steuer;Rajat Tewari;Rahul Tewari
Affiliations:
Department of Mechanical Engineering, Indian Institute of Technology Kanpur, Kanpur, India and Department of Business Technology, Aalto University, School of Economics, Helsinki, Finland;Department Banking and Finance, Terry College of Business, University of Georgia, Athens, Georgia;Benaras Hindu University, Benaras, India;Deutsche Bank Group, Mumbai, India
Venue:
EMO'11 Proceedings of the 6th international conference on Evolutionary multi-criterion optimization
Year:
2011

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Abstract

Bi-objective portfolio optimization for minimizing risk and maximizing expected return has received considerable attention using evolutionary algorithms. Although the problem is a quadratic programming (QP) problem, the practicalities of investment often make the decision variables discontinuous and introduce other complexities. In such circumstances, usual QP solution methodologies can not always find acceptable solutions. In this paper, we modify a bi-objective evolutionary algorithm (NSGA-II) to develop a customized hybrid NSGA-II procedure for handling situations that are non-conventional for classical QP approaches. By considering large-scale problems, we demonstrate how evolutionary algorithms enable the proposed procedure to find fronts, or portions of fronts, that can be difficult for other methods to obtain.