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Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/1181

Title: Optimal Weighting of Assets using a Multi-objective Evolutionary Algorithm
Authors: Mishra, S K
Panda, G
Meher, S
Sahu, S S
Keywords: Genetic algorithms
multiobjective optimization
Pareto-optimal solutions
global optimization
Crowding distance
Issue Date: 2009
Citation: International Journal of Recent Trends in Engineering, Vol 2, No. 5, November 2009
Abstract: Abstract— The problem of portfolio optimization is a well-known standard problem in financial world. It has received a lot of attention among many researchers. Choosing an optimal weighting of assets is a critical issue for which the decision maker takes several aspects into consideration. In this paper we consider a multi-objective portfolio assets selection problem where the total profit of is maximized while total risk to be minimized simultaneously. Three evolutionary algorithms i.e. Pareto Envelope-based Algorithm(PESA), Evolutionary Algorithm 2(SPEA2), Nondominated Sorting Genetic Algorithm II( NSGA II) for solving the bi-objective portfolio optimization problem has been applied. Performance comparison carried out in this paper by performing different numerical experiments. These experiments are performed using real-world data. The results show that NSGA-II outperforms other two for the considered test cases.
URI: http://hdl.handle.net/2080/1181
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