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Combining argumentation and hybrid evolutionary systems in a portfolio construction application

Spanoudakis Nikolaos I., Pendaraki Konstantina, Beligiannis Grigorios

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Περίληψη

In this paper we present an application for theconstruction of mutual fund portfolios. It is based on acombination of Intelligent Methods, namely an argumentationbased decision making framework and a forecasting algorithmcombining Genetic Algorithms (GA), MultiModel Partitioning(MMP) theory and Extended Kalman Filters (EKF). Theargumentation framework is employed in order to develop mutualfunds performance models and to select a small set of mutualfunds, which will compose the final portfolio. The forecastingalgorithm is employed in order to forecast the market status(inflating or deflating) for the next investment period. Theknowledge engineering approach and application developmentsteps are also discussed.

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