基于离散近似迭代法的多阶段M-SAD投资组合优化  

Discrete Approximate Iteration Method on the Mean-semi-absolute Deviation Multiperiod Portfolio Selection

作　　者：张鹏[1] 

机构地区：[1]武汉科技大学管理学院,武汉430081

出　　处：《科学技术与工程》2008年第19期5347-5351,共5页Science Technology and Engineering

基　　金：国家自然科学基金项目(70471077);武汉科技大学校基金项目(2008XY33)资助

摘　　要：提出了具有交易成本和交易量限制的多阶段均值-半绝对偏差(M-SAD)投资组合模型,并用自创算法——离散近似迭代方法求解。该算法的基本思路为:首先,将连续型状态变量离散化,根据网络图的构造方法将上述模型转化多阶段赋权有向图;其次,运用嘉量原理求出起点至终点的最长路程,即获得模型的一个可行解;最后,以该可行解为基础,继续迭代直到前后两个可行解非常接近。文章还证明了该方法的收敛性和复杂性。The muhiperiod mean-semi-absolute deviation portfolio selection model is proposed with the transaction costs and the constrainted on trade volumes and used special algorithm-the discrete approximate iteration method to solve it. Firstly, according to the network method, discretizes the state variables and transforms the model into multiperiod weighted digraph;Secondly, uses Jar-metric principle to solve the maximal path that is the admissible solution;At last, continues iterating until the two admissible solution is near based on the admissible solution. The convergence and complex of the method are also proved.

关 键 词：多阶段投资组合 均值-半绝对偏差 离散近似迭代方法 嘉量原理 旋转算法 

分 类 号：O157.6[理学—数学]