Portfolio optimization based on quadratic particle swarm optimization

Jiang Jinshan, Liao Wenzhi

Research output: Contribution to journalArticlepeer-review


Portfolio investment is a complicated combinatorial optimization problem,and is a NP-hard problem,which is difficult to be solved by traditional algorithm.In this paper,a quadratic particle swarm optimization (QPSO) is applied to solving the problem of portfolio investment optimization. In addition,self adapting parameters are applied.The result of the experiment shows that the QPSO can both escape local optimum and speed up global optimal convergence,and outperforms particle swarm optimization in some sense.
Original languageEnglish
Pages (from-to)161-163
Number of pages3
JournalComputer Applications and Software
Issue number6
Publication statusPublished - 30 Jun 2009


  • particle swarm optimization
  • portfolio investment
  • quadratic particle swarm optimization


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