Portfolio selection is a relevant problem arising in finance and economics. While its basic formulation can be efficiently solved through linear programming, its more practical and realistic variants, that include various kinds of constraints and objectives, have to be tackled by approximate algorithms. In this work, we present a hybrid technique that combines a local search, as master solver, with a quadratic programming procedure, as slave solver. Preliminary results show that the approach is very promising and achieves results comparable or superior with the state of the art solvers.
A Hybrid Solver for Constrained Portfolio Selection Problems -preliminary report / L.Di Gaspero; G.di Tollo; A.Roli; A.Schaerf. - ELETTRONICO. - (2007), pp. 1-8. (Intervento presentato al convegno Learning and Intelligent OptimizatioN LION 2007 tenutosi a Trento (Italia) nel 12-18 Febbraio 2007).
A Hybrid Solver for Constrained Portfolio Selection Problems -preliminary report
ROLI, ANDREA;
2007
Abstract
Portfolio selection is a relevant problem arising in finance and economics. While its basic formulation can be efficiently solved through linear programming, its more practical and realistic variants, that include various kinds of constraints and objectives, have to be tackled by approximate algorithms. In this work, we present a hybrid technique that combines a local search, as master solver, with a quadratic programming procedure, as slave solver. Preliminary results show that the approach is very promising and achieves results comparable or superior with the state of the art solvers.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
