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.
A Novel Multi Objective Genetic Algorithm for the Portfolio Optimization / Bevilacqua, Vitoantonio; Pacelli, Vincenzo; Saladino, Stefano (LECTURE NOTES IN COMPUTER SCIENCE). - In: Advanced Intelligent Computing : 7th International Conference, ICIC 2011, Zhengzhou, China, August 11-14, 2011. Revised Selected Papers / [a cura di] De-Shuang Huang; Yong Gan; Vitoantonio Bevilacqua; Juan Carlos Figueroa. - STAMPA. - Berlin; Heidelberg : Springer, 2011. - ISBN 978-3-642-24727-9. - pp. 186-193 [10.1007/978-3-642-24728-6_25]
A Novel Multi Objective Genetic Algorithm for the Portfolio Optimization
Vitoantonio Bevilacqua;
2011-01-01
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.