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 |
Appears in Collections: | Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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sudhanshu2.pdf | 344.07 kB | Adobe PDF | View/Open |
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