An extended TDM method under probabilistic interval-valued hesitant fuzzy environment for stock selection

被引:1
|
作者
Noor, Qasim [1 ]
Rashid, Tabasam [2 ]
Husnine, Syed Muhammad [1 ]
机构
[1] Natl Univ Comp & Emerging Sci, Dept Sci & Humanities, Lahore, Pakistan
[2] Univ Management & Technol, Sch Sci, Dept Math, Lahore, Pakistan
来源
PLOS ONE | 2021年 / 16卷 / 05期
关键词
VALUE-AT-RISK; INFORMATION AGGREGATION; PREFERENCE RELATIONS; DECISION-MAKING; SETS; CONSISTENCY; OPERATORS; DISTANCE;
D O I
10.1371/journal.pone.0252115
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Generally, in real decision-making, all the pieces of information are used to find the optimal alternatives. However, in many cases, the decision-makers (DMs) only want "how good/bad a thing can become." One possibility is to classify the alternatives based on minimum (tail) information instead of using all the data to select the optimal options. By considering the opportunity, we first introduce the value at risk (VaR), which is used in the financial field, and the probabilistic interval-valued hesitant fuzzy set (PIVHFS), which is the generalization of the probabilistic hesitant fuzzy set (PHFS). Second, deemed value at risk (DVaR) and reckoned value at risk (RVaR) are proposed to measure the tail information under the probabilistic interval-valued hesitant fuzzy (PIVHF) environment. We proved that RVaR is more suitable than DVaR to differentiate the PIVHFEs with example. After that, a novel complete group decision-making model with PIVHFS is put forward. This study aims to determine the most appropriate alternative using only tail information under the PIVHF environment. Finally, the proposed methods' practicality and effectiveness are tested using a stock selection example by selecting the ideal stock for four recently enrolled stocks in China. By using the novel group decision-making model under the environment of PIVHFS, we see that the best stock is E-4 when the distributors focus on the criteria against 10% certainty degree and E-1 is the best against the degree of 20%, 30%, 40% and 50% using the DVaR method. On the other hand when RVaR method is used then the best alternative is E-4 and the worst is E-2 against the different certainty degrees. Furthermore, a comparative analysis with the existing process is presented under the PHF environment to illustrate the effectiveness of the presented approaches.
引用
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页数:24
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