Fuzzy multi-criteria decision-making for evaluating mutual fund strategies

Investors often need to evaluate investment strategies according to their own subjective preferences based upon various criteria. This situation can be regarded as a Fuzzy Multiple Criteria Decision-Making (FMCDM) problem. The purpose of this study is to propose an FMCDM approach with fuzzy integral. This approach relaxes the independence assumption among criteria for the evaluation of the Multiple Criteria Decision-Making (MCDM) problems, which is oftentimes the basic assumption in applying hierarchical system for evaluating the strategies of selecting investment style. We also employ Triangular Fuzzy Numbers (TFNs) to represent the decision-makers' subjective preferences on the criteria, as well as for the criteria measurements to evaluate mutual funds investment style. To achieve this objective, first, we employ factor analysis to extract four independent common factors from those criteria. Second, we construct the evaluation frame using hierarchical system composed of four common factors with 16 evaluation criteria, and then derive the relative weights with respect to the considered criteria. Third, the synthetic utility value corresponding to each mutual fund's investment style is aggregated by the fuzzy weights with fuzzy performance values. Finally, we compare with empirical data and find that the model of FMCDM predicts the rate of return very accurately in certain ranges of lambda, hence the nonadditive fuzzy integral technique is an effective method for evaluating mutual funds' strategy.