基于粒子群算法的证券组合投资模型的研究  

Portfolio Investment Model Based on Particle Swarm Optimization

作　　者：刘侠[1] 初红霞[1] 王科俊[1] 

机构地区：[1]哈尔滨理工大学自动化学院,黑龙江哈尔滨150080

出　　处：《商业研究》2006年第16期49-51,共3页Commercial Research

基　　金：哈尔滨市青年科学研究基金;项目编号:2004AFQXJ046

摘　　要：从证券组合模型的概念,给出证券组合多目标决策模型。并用模糊优选法将证券组合多目标优化转化为单目标优化。同时,重点描述了粒子群算法,并采用自适应变异的粒子群算法对证券组合投资模型进行求解,最后编程实现证券组合模型的最优解,试验结果表明此方法取得了较好的效果。The paper introduces the concept of portfolio＇s model and describes multiple objective decision model about it in detail.Multiple- objective optimal problem is converted into simple objective optimization by using the fuzzy optimum seeking method.h emphasizes particle swarm optimization algorithm in succession.Portfolio investment model can be established with self- adapting mutation＇s PSO. Experimental result shows that the method acquires the preferable effect.

关 键 词：证券组合 粒子群算法 自适应变异 

分 类 号：F830.91[经济管理—金融学]