摘要
在传统Markowitz投资组合模型中考虑了最小交易量、交易费用以及最大投资上限等实际因素,得到了一个改进的投资组合模型。该模型是一个非线性整数规划问题,传统算法难以有效求解。为此,设计了一种基于整数编码的遗传算法求解该模型。实际算例表明,所提出的算法是有效的。
Based on the classical Markowitz portfolio model, an improved portfolio model is proposed for portfolio selection with minimum transaction lots, transaction costs and upper limit on the maximum amount of invested capital in any security. The portfolio selection modelling,as a nonlinear integer programming problem, is difficult with the traditional optimization methods. A genetic algorithms based on integer coding genetic operators is designed to propose the model. It is illustrated via a numerical example that the genetic algorithms can be used to solve the portfolio optimization problem efficiently.
出处
《系统工程》
CSCD
北大核心
2005年第8期68-72,共5页
Systems Engineering
基金
国家自然科学基金资助项目(70301005)
教育部南开-天津大学刘徽应用数学中心资助项目
关键词
投资组合
最小交易量
交易费用
遗传算法
Portfolio Selection
Minimum Transaction Lots
Transaction Costs
Genetic Algorithm
