Asset portfolio optimization using support vector machines and real‐coded genetic algorithm

This paper presents an integrated approach for portfolio selection in a multicriteria decision making framework. Firstly, we use Support Vector Machines for classifying financial assets in three pre‐defined classes, based on their performance on some key financial criteria. Next, we employ Real‐Coded Genetic Algorithm to solve a mathematical model of the multicriteria portfolio selection problem in the respective classes incorporating investor‐preferences.