Abstract
In this paper we propose a new implementation of a multi objective genetic algorithm that handles constrained problems to approach the financial problem of the portfolio optimization. The objective of the paper is to propose and empirically apply a new multi-objective genetic algorithm for portfolio optimization extending the Markowitz mean-variance model ([1,2] Markowitz, 1952 and 1959). At the end of the paper the obtained results are discussed and compared with non linear other different techniques.
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Bevilacqua, V., Pacelli, V., Saladino, S. (2011). A Novel Multi Objective Genetic Algorithm for the Portfolio Optimization. In: Huang, DS., Gan, Y., Bevilacqua, V., Figueroa, J.C. (eds) Advanced Intelligent Computing. ICIC 2011. Lecture Notes in Computer Science, vol 6838. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24728-6_25
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DOI: https://doi.org/10.1007/978-3-642-24728-6_25
Publisher Name: Springer, Berlin, Heidelberg
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