Application of Multi-Objective Evolutionary Algorithms in Computational Finance

Abstract

Application of Multiobjective evolutionary algorithms (MOEAs) in diversified domains has gained popularity in wide area ranging from engineering and computer science to ecology, sociology and medicine field. From these diversified application areas of evolutionary algorithms, computational finance constitutes a very promising field. The use of evolutionary algorithms for solving multi-objective optimization problem emerges as a potential field of research in recent years. This paper deals with application of MOEAs for different problems in computational finance. Different applications are explained briefly and exhaustive simulation study has been carried out for one particular application i.e. investment portfolio optimization. In this paper the Portfolio optimization is solved using two different multi-objective algorithms SPEA2 and NSGA-II. Their performances have been compared in terms of Pareto fronts, the delta, and C and S metrics.