Abstract

The paper presents a decision support method for financial investment decision making - an area where uncertainty is inherent. Investment decision support requires understandable tools able to deal with imprecision and provide easily interpretable outputs to the decision makers. We therefore propose a two-step decision support model that employs two different mathematical approaches. The first step represents investment strategy recommendation and is realised on the base of Mamdani's inference using linguistic fuzzy rules. The second step involves a preselection of mutual funds in accordance with the investment strategy proposed in the first step and provides decision support for mutual funds selection based on multiple criteria (fuzzy OWA aggregation is used). The output is presented to the investor as a picture (graphical representation of fuzzy numbers) with linguistic labels and real number representations (defuzzified values) of the fuzzy outputs. A numerical example of mutual funds selection using FuzzME software is presented.

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