Multi-stage portfolio optimization using quantum-behaved partical swarm optimization
基于QPSO算法的多阶段投资组合优化

The method of decision-making in the field of multi-stage portfolio optimization using Quantum-behaved Partical Swarm Optimization(QPSO) was studied.Its objective function was to maximize one's economic utility or end-of-period wealth.How to use QPSO to find best portfolio according to objective function was introduced.By comparing the expect return and their variances that come from optimizing the allocation of cash and various stocks in the market of USA,QPSO algorithm with genetic algorithms was demonstrated superior to genetic algorithms.