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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/1181
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| 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
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| sudhanshu2.pdf | | 344Kb | Adobe PDF | View/Open |
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