Utility exchange traded fund performance evaluation. A comparative approach using grey relational analysis and data envelopment analysis modelling

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.