Comparison of Classic Mean-Variance and Fuzzy Model Approaches to Portfolio Selection Problem

Selection of an efficient portfolio is a sophisticated process assuming decision making on proper distribution of funds based on possible expected rates of return and risk. In general, portfolio theory and relevant topics are among the most investigated issues in economic and financial articles. As a rule, decision maker uses past historical data of financial securities to make assumptions on expected returns and risk. Obviously, investors often deal with imprecise data while making decisions. To overcome such difficulties some researchers, suggest combination of the classic mean variance portfolio model with other approaches. It seems difficult to choose a proper approach to investment portfolio selection problem. The comparison of classic mean-variance model and mean-variance model with combination fuzzy approach performed in this study contributes to actuality of the paper. Modeling of sample investment portfolio is implemented by using statistical data obtained from Yahoo Finance web-platform and expert opinion. In the classic approach MS Excel is used to perform calculations and construct efficient frontier. The software based on C# programming language is developed for defining efficient portfolios and constructing fuzzy efficient frontier in combined approach. The comparison of the two methods shows the efficiency of fuzzy approach. It provides more flexibility to investors and represents an interval within return and risk of efficient portfolios might vary. Investors may choose a portfolio which best suits their return expectation and risk preferences from a given set of efficient portfolios comprising efficient frontier.