A novel robust network data envelopment analysis approach for performance assessment of mutual funds under uncertainty

被引：19

作者：

Peykani, Pejman ^{[1
]}

Emrouznejad, Ali ^{[2
]}

Mohammadi, Emran ^{[1
]}

Gheidar-Kheljani, Jafar ^{[3
]}

机构：

[1] Iran Univ Sci & Technol, Sch Ind Engn, Tehran, Iran

[2] Univ Surrey, Surrey Business Sch, Guildford, Surrey, England

[3] Malek Ashtar Univ Technol, Management & Ind Engn Dept, Tehran, Iran

来源：

ANNALS OF OPERATIONS RESEARCH | 2024年 / 339卷 / 03期

关键词：

Mutual fund; Network data envelopment analysis; Robust optimization; Extended two-stage structure; Uncertainty; DEA MODELS; EFFICIENCY DECOMPOSITION; OPTIMIZATION; APPRAISAL; COMPANIES;

D O I：

10.1007/s10479-022-04625-3

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：

Mutual fund (MF) is one of the applicable and popular tools in investment market. The aim of this paper is to propose an approach for performance evaluation of mutual fund by considering internal structure and financial data uncertainty. To reach this goal, the robust network data envelopment analysis (RNDEA) is presented for extended two-stage structure. In the RNDEA method, leader-follower (non-cooperative game) and robust optimization approaches are applied in order to modeling network data envelopment analysis (NDEA) and dealing with uncertainty, respectively. The proposed RNDEA approach is implemented for performance assessment of 15 mutual funds. Illustrative results show that presented method is applicable and effective for performance evaluation and ranking of MFs in the presence of uncertain data. Also, the results reveal that the discriminatory power of robust NDEA approach is more than the discriminatory power of deterministic NDEA models.

引用

页码：1149 / 1175

页数：27

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