Affiliations: [a] Applied Mathematics and Computers Laboratory, Department of Sciences, Technical University of Crete, University Campus, 73100, Kounoupidiana, Greece | [b] Department of Business, Administration of Food and Agricultural Enterprises, University of Ioannina, G. Seferi 2, 30100 Agrinio, Greece | University of Patras, School of Engineering, Dept of Computer Engineering & Informatics, 26500 Patras, Greece
Abstract: In the current contribution, an application for constructing mutual fund portfolios is presented. This approach comprises several Intelligent Methods, namely an argumentation based decision making framework and a hybrid evolutionary forecasting algorithm which combines Genetic Algorithms (GA), MultiModel Partitioning (MMP) theory and Extended Kalman Filters (EKF). Specifically, the argumentation framework is employed in order to develop mutual funds performance models and select a small set of mutual funds, which will compose the final portfolio. On the other hand, the hybrid evolutionary forecasting algorithm is applied in order to forecast the market status (inflating or deflating) for the next investment period. The knowledge engineering approach and application development steps are also presented and discussed.