Evolutionary Algorithms and the Cardinality Constrained Portfolio Optimization Problem
2004; Springer Nature; Linguagem: Inglês
10.1007/978-3-642-17022-5_33
ISSN2197-9294
AutoresFelix Streichert, Holger Ulmer, Andreas Zell,
Tópico(s)Scheduling and Optimization Algorithms
ResumoWhile the unconstrained portfolio optimization problem can be solved efficiently by standard algorithms, this is not the case for the portfolio optimization problem with additional real world constraints like cardinality constraints, buy-in thresholds, roundlots etc. In this paper we investigate two extensions to Evolutionary Algorithms (EA) applied to the portfolio optimization problem. First, we introduce a problem specific EA representation and then we add a local search for feasible solutions to improve the performance of the EA. All algorithms are compared on the constrained and unconstrained portfolio optimization problem.
Referência(s)