ASSESSING EQUITY MUTUAL FUNDS' PERFORMANCE USING A MULTICRITERIA METHODOLOGY: A COMPARATIVE ANALYSIS

K. Pendaraki, M. Doumpos and C. Zopounidis
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K. Pendaraki: Technical University of Crete, Dept. of Production Engineering and Management, Financial Engineering Laboratory, University Campus, 73100 Chania, Greece
M. Doumpos: Technical University of Crete, Dept. of Production Engineering and Management, Financial Engineering Laboratory, University Campus, 73100 Chania, Greece
C. Zopounidis: Technical University of Crete, Dept. of Production Engineering and Management, Financial Engineering Laboratory, University Campus, 73100 Chania, Greece

Chapter 5 in Supply Chain and Finance, 2004, pp 69-90 from World Scientific Publishing Co. Pte. Ltd.

Abstract: AbstractBecoming more and more popular, mutual funds have begun to play an increasingly important role in financial markets. In particular, the evaluation of the performance of mutual funds has been a very interesting research topic not only for researchers, but also for managers of financial, banking and investment institutions. This chapter explores the performance of a non-parametric approach in developing mutual fund's performance models. The proposed approach is based on the UTADIS (Utilités Additives DIScriminates) multicriteria decision aid method. The data set used to examine the mutual funds' performance consists of daily data of the Greek domestic equity mutual funds, and is derived from the Alpha Trust Mutual Fund Management Company S.A. (A.E.D.A.K.). The sample consisting of 33 mutual funds is used to estimate the performance of the method in classifying the funds into two groups. A cross-validation procedure is employed to evaluate the predictive performance of the models and a comparison with linear discriminant analysis is also performed. The results indicate the superiority of the UTADIS method as opposed to the traditional discrimination technique, while the developed models are accurate in classifying the total sample correctly with rate approximately 80% (overall accuracy).

Keywords: Finance; Supply Chain; E-Commerce; Optimization; Mathematical Modeling; Operations Research (search for similar items in EconPapers)
Date: 2004
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