Name
Title | ||
|---|---|---|
Solving the multi-stage portfolio optimization problem with a novel particle swarm optimization |
Abstract | ||
|---|---|---|
Solving the multi-stage portfolio optimization (MSPO) problem is very challenging due to nonlinearity of the problem and its high consumption of computational time. Many heuristic methods have been employed to tackle the problem. In this paper, we propose a novel variant of particle swarm optimization (PSO), called drift particle swarm optimization (DPSO), and apply it to the MSPO problem solving. The classical return-variance function is employed as the objective function, and experiments on the problems with different numbers of stages are conducted by using sample data from various stocks in S&P 100 index. We compare performance and effectiveness of DPSO, particle swarm optimization (PSO), genetic algorithm (GA) and two classical optimization solvers (LOQO and CPLEX), in terms of efficient frontiers, fitness values, convergence rates and computational time consumption. The experiment results show that DPSO is more efficient and effective in MSPO problem solving than other tested optimization tools. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1016/j.eswa.2010.11.061 | Expert Syst. Appl. |
Keywords | Field | DocType |
classical return-variance function,heuristic methods,multi-stage portfolio optimization,efficient frontier,drift particle swarm optimization,computational time,stochastic programming,particle swarm optimization,novel particle swarm optimization,risk management,optimization tool,multi-stage portfolio optimization problem,classical optimization solvers,computational time consumption,mspo problem,objective function,genetic algorithm,convergence rate,portfolio optimization,indexation,variance function | Particle swarm optimization,Heuristic,Mathematical optimization,Computer science,Multi-swarm optimization,Portfolio optimization,Artificial intelligence,Stochastic programming,Optimization problem,Machine learning,Genetic algorithm,Metaheuristic | Journal |
Volume | Issue | ISSN |
38 | 6 | Expert Systems With Applications |
Citations | PageRank | References |
8 | 0.45 | 14 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jun Sun | 1 | 207 | 12.29 |
| Wei Fang | 2 | 339 | 19.89 |
| Xiaojun Wu | 3 | 230 | 11.79 |
| Choi-Hong Lai | 4 | 101 | 12.01 |
| Wenbo Xu | 5 | 370 | 23.34 |