In this paper, a maximum likelihood estimation and a minimum entropy estimation for the expected value and variance of normal fuzzy variable are discussed within the framework of credibility theory. As an application, a credibilistic portfolio selection model is proposed, which is an improvement over the traditional models as it only needs the predicted values on the security returns instead of...

In the present paper an approaches to the definition of numerical charac-teristics of fuzzy random variables are analyzed and proposed. Appropriatemethods of its calculation, in particular within the framework of shift-scaled representation are obtained. Principles of decision making in fuzzyrandom environment are formulated. Possibilistic-probabilistic models ofportfolio an...

In this research, we proposed a new metaheuristic technique for stock portfolio multi-objective optimization employing the combination of Strength Pareto Evolutionary Algorithm (SPEA), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Arbitrage Pricing Theory (APT). To generate the more precise model, ANFIS has implemented to envisage long-term movement values of the Tehran Stock Exchange (TSE)...

The portfolio optimization is one of the fundamental problems in asset management that aims to reduce the risk of an investment by diversifying it into assets expected to fluctuate independently. A portfolio is a grouping of financial assets such as stocks, bonds, commodities, currencies and cash equivalents, as well as their funds counterparts, including mutual, exchange- traded and closed fun...

In this paper, we carry out the numerical study of a fuzzy portfolio selection model where the objective is to minimize the downside risk and the rates of returns on securities are approximated by means of LR-fuzzy numbers of trapezoidal form. Data from 96 securities over 195 month are used to compare the selected portfolios with a simple utility function and with the outof-sample data as well ...

In this paper a data mining approach for classification of stocks into clusters is presented. After classification, the stocks could be selected from these groups for building a portfolio. It meets the criterion of minimizing the risk by diversification of a portfolio. The clustering approach categorizes stocks on certain investment criteria. We have used stock returns at different times along ...