Abstract
The aim of this paper is to assess the efficiency of a set of 62 precious metal mutual funds (PMMFs) and to explain performance differences between funds using weighted additive data envelopment analysis (DEA) and Tobit regression, respectively. The contribution of this paper is twofold: to provide for the first-time metrics of the relative performance of PMMFs using a particular weighted additive model, namely the range-adjusted measure (RAM), and to explain the performance of the funds by the use of a Tobit model. Results do not suggest positive linkages between RAM-based and standard fund performance metrics (Sharpe ratio and Jensen’s alpha). Moreover, for the sample inefficient funds the mean–variance performance hypothesis does not hold. In addition, fund performance based on RAM can be explained by the persistence of the fund and the beta coefficient.
Highlights
In recent years, investment in precious metals has increased with a marked transition of resources from physically observable to financial investments
There are alternative financial investment vehicles available to precious metal investors, the current paper focuses on the performance appraisal of precious metal mutual funds (PMMFs)
The current paper combines data envelopment analysis (DEA) with the parametric Tobit regression to analyze the performance of a sample of PMMFs
Summary
Investment in precious metals has increased with a marked transition of resources from physically observable to financial investments. Recent surveys on gold (O’Connor et al 2015) and precious white metals (i.e., silver, platinum, and palladium) research (Vigne et al 2017) favor gold mutual funds and exchange traded funds (ETFs) as diversifiers and support a strong relationship between gold and silver ETFs return. The financial appraisal of a mutual fund scheme involves data gathering and the application of selected techniques, and because of its academic and practical value, it is a crucial area of research in finance. Two main research streams on mutual fund performance appraisal are identified in the literature: the first stream includes methods based on Capital Asset Pricing Model (CAPM) and utility theory, and the second stream involves operation research methods such as data envelopment analysis (DEA) (Bravo et al 2012)
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