The popularity of mutual funds, which are necessarily portfolios, has been drawing more attention from the people of India over the last three decades. In a mutual fund, one can invest his or her money in the securities of different sectors traded mainly in the stock exchange markets to get expected return bearing tolerable risks. A mutual fund other than the passive mutual funds is directed by an active fund manager. The performance of a mutual fund depends on the shares and securities of different companies it contains and the fund manager's performance also. Risk and return can be measured based on different criteria. Before investment, one should select such a mutual fund that can fulfill his or her anticipation as much as possible within the risk–return skeleton. Therefore the selection of a mutual fund is rigorously a multicriteria decision making. This paper has considered five open-ended, large-cap, direct, suspended sales mutual funds for the research work. In the first stage, we have shortlisted the more crucial criteria comparatively from a list of criteria with the help of the Fuzzy Analytic Hierarchy Process. In the second stage, we have applied the Pythagorean fuzzy Gray Relation Analysis approach to determine the weights of shortlisted criteria as well as the rank of those mutual funds. Finally, a comparison has been drawn between the present model and the Pythagorean fuzzy Interactive Multicriteria Decision-Making model, to show the effectiveness of the present model.

中文翻译：

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投资组合选择作为具有 GRA 和 FAHP 框架的勾股模糊环境中的多准则群决策

在过去的三年中，共同基金（必然是投资组合）的流行引起了印度人民的更多关注。在共同基金中，人们可以将资金投资于主要在证券交易所市场交易的不同行业的证券，以获得可承受风险的预期回报。被动共同基金以外的共同基金由主动基金经理管理。共同基金的表现取决于它所包含的不同公司的股票和证券以及基金经理的表现。可以根据不同的标准来衡量风险和回报。在投资之前，应该选择这样一种共同基金，它可以在风险-回报框架内尽可能地满足他或她的预期。因此，共同基金的选择是严格的多标准决策。本文为研究工作考虑了五只开放式、大盘股、直接、暂停销售的共同基金。在第一阶段，我们在模糊层次分析过程的帮助下从标准列表中比较关键的标准入围。在第二阶段，我们应用了勾股模糊灰色关联分析方法来确定入围标准的权重以及这些共同基金的排名。最后，将本模型与勾股模糊交互式多准则决策模型进行了比较，以表明本模型的有效性。在第一阶段，我们在模糊层次分析过程的帮助下从标准列表中比较关键的标准入围。在第二阶段，我们应用了勾股模糊灰色关联分析方法来确定入围标准的权重以及这些共同基金的排名。最后，将本模型与勾股模糊交互式多准则决策模型进行了比较，以表明本模型的有效性。在第一阶段，我们在模糊层次分析过程的帮助下从标准列表中比较关键的标准入围。在第二阶段，我们应用了勾股模糊灰色关联分析方法来确定入围标准的权重以及这些共同基金的排名。最后，将本模型与勾股模糊交互式多准则决策模型进行了比较，以表明本模型的有效性。我们已经应用了勾股模糊灰色关系分析方法来确定入围标准的权重以及这些共同基金的排名。最后，将本模型与勾股模糊交互式多准则决策模型进行了比较，以表明本模型的有效性。我们已经应用了勾股模糊灰色关系分析方法来确定入围标准的权重以及这些共同基金的排名。最后，将本模型与勾股模糊交互式多准则决策模型进行了比较，以表明本模型的有效性。