Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/257665 
Year of Publication: 
2019
Citation: 
[Journal:] International Journal of Financial Studies [ISSN:] 2227-7072 [Volume:] 7 [Issue:] 4 [Article No.:] 67 [Publisher:] MDPI [Place:] Basel [Year:] 2019 [Pages:] 1-9
Publisher: 
MDPI, Basel
Abstract: 
Selecting funds is a common problem for investors who use published available data on fund indicators while they are selecting the funds. Since this process deals with more than one indicator, the investing issue becomes multi-criteria decision-making (MCDM) problem for the investors. Therefore, the purpose of this paper is to propose an effective approach that integrates grey relational analysis (GRA) and data envelopment analysis (DEA) for selecting the best utility exchange traded funds (ETFs). The current study uses GRA for deriving the grade relational coefficients and then puts them in the output side of competing no-input DEA models to derive weighed grey relational grades. Moreover, the ETFs are also evaluated by selected DEA models. This research is implemented with real data on utility ETFs available for three consecutive years (2008-2010). The results show that the top ETFs identified by the GRA-DEA approach are also DEA efficient. The proposed GRA-DEA approach is superior to conventional DEA as regards the fund ranking and therefore, it seems to be effective as a picking fund tool.
Subjects: 
data envelopment analysis
efficiency
generalized proportional distance function
grey relational analysis
utility exchange traded funds
JEL: 
C14
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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