Portfolio optimization under lower partial risk measures

被引：8

作者：

Konno H. ^{[1
,2
]}

Waki H. ^{[3
]}

Yuuki A. ^{[4
]}

机构：

[1] Department of Industrial and Systems Engineering, Chuo University, Bunkyo-ku Tokyo 112-8551

[2] Research Center for Financial Engineering, Institute of Economic Research, Kyoto University

[3] Department of Mathematical and Computing Science, Tokyo Institute of Technology

来源：

Asia-Pacific Financial Markets | 2002年 / 9卷 / 2期

关键词：

Conditional value-at-risk; Dense linear programming problem; Factor model; Lower partial risk; Lower-semi absolute deviation; Portfolio management;

D O I：

10.1023/A:1022238119491

中图分类号：

学科分类号：

摘要：

Portfolio management using lower partial risk (downside risk) measures is attracting more attention of practitioners in recent years. The purpose of this paper is to review important characteristics of these risk measures and conduct simulation using four alternative measures, lower semi-variance, lower semi-absolute deviation, first order below target risk and conditional value-at-risk. We will show that these risk measures are useful to control downside risk when the distribution of assets is non-symmetric. Further, we will propose a computational scheme to resolve the difficulty associated with solving a large dense linear programming problems resulting from these models. We will demonstrate that this method can in fact solve problems consisting of 104 assets and 105 scenarios within a practical amount of CPU time. © 2002 Kluwer Academic Publishers.

引用

页码：127 / 140

页数：13

共 17 条

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