Experimental study on a hybrid nature-inspired algorithm for financial portfolio optimization

Authors:
Giorgos Giannakouris;Vassilios Vassiliadis;George Dounias
Affiliations:
Management and Decision Engineering Laboratory, Department of Financial and Management Engineering, University of the Aegean, Greece;Management and Decision Engineering Laboratory, Department of Financial and Management Engineering, University of the Aegean, Greece;Management and Decision Engineering Laboratory, Department of Financial and Management Engineering, University of the Aegean, Greece
Venue:
SETN'10 Proceedings of the 6th Hellenic conference on Artificial Intelligence: theories, models and applications
Year:
2010

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Abstract

Hybrid intelligent schemes have proven their efficiency in solving NP-hard optimization problems Portfolio optimization refers to the problem of finding the optimal combination of assets and their corresponding weights which satisfies a specific investment goal and various constraints In this study, a hybrid intelligent metaheuristic, which combines the Ant Colony Optimization algorithm and the Firefly algorithm, is proposed in tackling a complex formulation of the portfolio management problem The objective function under consideration is the maximization of a financial ratio which combines factors of risk and return At the same time, a hard constraint, which refers to the tracking ability of the constructed portfolio towards a benchmark stock index, is imposed The aim of this computational study is twofold Firstly, the efficiency of the hybrid scheme is highlighted Secondly, comparison results between alternative mechanisms, which are incorporated in the main function of the hybrid scheme, are presented.