Multiperiod Mean-Variance Portfolio Optimization via Market Cloning

被引：5
|
作者：
Ankirchner, Stefan [1 ]
Dermoune, Azzouz [2 ]
机构：
[1] Univ Bonn, Hausdorff Ctr Math, Inst Angew Math, D-53115 Bonn, Germany
[2] Univ Sci & Technol Lille, UFR Math, Lab Paul Painleve, CNRS,UMR 8524, F-59655 Villeneuve Dascq, France
来源：
APPLIED MATHEMATICS AND OPTIMIZATION | 2011年 / 64卷 / 01期
关键词：
Dynamic programming; Mean variance optimization; Optimal portfolios; Market clones; Independent returns; Empirical mean;
D O I：
10.1007/s00245-011-9134-0
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
The problem of finding the mean variance optimal portfolio in a multiperiod model can not be solved directly by means of dynamic programming. In order to find a solution we therefore first introduce independent market clones having the same distributional properties as the original market, and we replace the portfolio mean and variance by their empirical counterparts. We then use dynamic programming to derive portfolios maximizing a weighted sum of the empirical mean and variance. By letting the number of market clones converge to infinity we are able to solve the original mean variance problem.
引用
收藏
页码：135 / 154
页数：20
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