Multiobjective portfolio optimization using coherent fuzzy numbers in a credibilistic environment

被引:13
|
作者
Mehlawat, Mukesh K. [1 ]
Gupta, Pankaj [1 ]
Khan, Ahmad Z. [1 ]
机构
[1] Univ Delhi, Dept Operat Res, RZ-26P-21,St 34,Indra Pk, New Delhi 110045, India
关键词
coherent fuzzy numbers; credibility function; mean– mean sabsolute‐ semideviation– skewness model; multiobjective programming; real‐ coded genetic algorithm; PROGRAMMING-MODEL; SELECTION;
D O I
10.1002/int.22352
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we propose a new credibility function for a fuzzy variable that can accommodate the attitude of the investor (pessimistic, optimistic, or neutral) along with capturing the return expectations. We use an adaptive index, which the investors can use to specify their general perception of the financial market. We extend the classic mean-variance model so that it provides greater flexibility to the investors in specifying their requirements viz., level of diversification, minimum and maximum level of investment in a particular asset, and the skewness requirement. We also replace variance with mean-absolute semideviation as a measure of quantifying risk, which is more realistic, and solve the resultant multiobjective credibility model with a real-coded genetic algorithm. Numerical examples have been provided at the end to illustrate the methodology and advantages of the model.
引用
收藏
页码:1560 / 1594
页数:35
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