A novel portfolio selection model in a hybrid uncertain environment
被引:55
作者:
Li, Jun
论文数: 0引用数: 0
h-index: 0
机构:
Sichuan Univ, Sch Business & Adm, Uncertainty Decis Making Lab, Chengdu 610064, Sichuan, Peoples R China
Univ Elect Sci & Technol China, Sch Management, Chengdu 610054, Sichuan, Peoples R ChinaSichuan Univ, Sch Business & Adm, Uncertainty Decis Making Lab, Chengdu 610064, Sichuan, Peoples R China
Li, Jun
[1
,2
]
Xu, Jiuping
论文数: 0引用数: 0
h-index: 0
机构:
Sichuan Univ, Sch Business & Adm, Uncertainty Decis Making Lab, Chengdu 610064, Sichuan, Peoples R ChinaSichuan Univ, Sch Business & Adm, Uncertainty Decis Making Lab, Chengdu 610064, Sichuan, Peoples R China
Xu, Jiuping
[1
]
机构:
[1] Sichuan Univ, Sch Business & Adm, Uncertainty Decis Making Lab, Chengdu 610064, Sichuan, Peoples R China
[2] Univ Elect Sci & Technol China, Sch Management, Chengdu 610054, Sichuan, Peoples R China
portfolio selection;
fuzzy random variable;
expectation;
variance;
efficient frontier;
FUZZY RANDOM-VARIABLES;
EUROPEAN OPTIONS;
METHODOLOGY;
VALUATION;
VARIANCE;
D O I:
10.1016/j.omega.2007.06.002
中图分类号:
C93 [管理学];
学科分类号:
12 ;
1201 ;
1202 ;
120202 ;
摘要:
The future returns of each securities cannot be correctly reflected by the securities data in the past, therefore the statistical techniques and the experts' judgement and experience are combined together to estimate the security returns ill file future. In this paper. the returns of each securities are assumed to be fuzzy random variables, then following the ideas of mean variance model a new portfolio selection model in a hybrid uncertain environment is proposed. Moreover, the;lambda-mean variance efficient frontiers and lambda-mean variance efficient portfolios are defined, and the properties of lambda-mean variance efficient portfolios located on different lambda-mean variance efficient frontiers are discussed. Finally, a numerical example is presented to illustrate the proposed portfolio selection model. Oil the basis of the results, we can conclude that the proposed model can provide the more flexible results. (c) 2007 Elsevier Ltd. All rights reserved.