Hybrid Local Search for Constrained Financial Portfolio Selection Problems

Authors:
Luca Gaspero;Giacomo Tollo;Andrea Roli;Andrea Schaerf
Affiliations:
DIEGM, Università degli Studi di Udine, via delle Scienze 208, I-33100, Udine, Italy;Dipartimento di Scienze, Università "G.D'Annunzio", viale Pindaro 42, I-65127, Pescara, Italy;DEIS, Alma Mater Studiorum Università di Bologna, via Venezia 52, I-47023 Cesena, Italy;DIEGM, Università degli Studi di Udine, via delle Scienze 208, I-33100, Udine, Italy
Venue:
CPAIOR '07 Proceedings of the 4th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Year:
2007

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Abstract

Portfolio selection is a relevant problem arising in finance and economics. While its basic formulations can be efficiently solved through linear or quadratic programming, its more practical and realistic variants, which include various kinds of constraints and objectives, have in many cases to be tackled by approximate algorithms. In this work, we present a hybrid technique that combines a local search, as mastersolver, with a quadratic programming procedure, as slavesolver. Experimental results show that the approach is very promising and achieves results comparable with, or superior to, the state of the art solvers.