Low order-value approach for solving VaR-constrained optimization problems

被引：10

作者：

Birgin, E. G. ^{[1
]}

Bueno, L. F. ^{[2
]}

Krejic, N. ^{[3
]}

Martinez, J. M. ^{[2
]}

机构：

[1] Univ Sao Paulo, Dept Comp Sci IME USP, BR-05508090 Sao Paulo, Brazil

[2] Univ Estadual Campinas, Inst Math Stat & Sci Comp IMECC, Dept Appl Math, BR-13083859 Campinas, SP, Brazil

[3] Univ Novi Sad, Dept Math & Informat, Novi Sad 21000, Serbia

来源：

JOURNAL OF GLOBAL OPTIMIZATION | 2011年 / 51卷 / 04期

基金：

巴西圣保罗研究基金会;

关键词：

Optimization; Augmented Lagrangian; Order-value optimization; Low order-value optimization; Value at risk; Numerical algorithms; LINEAR-DEPENDENCE CONDITION; ALPHA-BB; PORTFOLIO OPTIMIZATION; RISK; SELECTION; NLPS;

D O I：

10.1007/s10898-011-9656-7

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

In Low Order-Value Optimization (LOVO) problems the sum of the r smallest values of a finite sequence of q functions is involved as the objective to be minimized or as a constraint. The latter case is considered in the present paper. Portfolio optimization problems with a constraint on the admissible Value at Risk (VaR) can be modeled in terms of a LOVO problem with constraints given by Low order-value functions. Different algorithms for practical solution of this problem will be presented. Using these techniques, portfolio optimization problems with transaction costs will be solved.

引用

页码：715 / 742

页数：28

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