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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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| DC Field | Value | Language |
|---|
| contributor.author | Mishra, S K | - |
| contributor.author | Panda, G | - |
| contributor.author | Meher, S | - |
| contributor.author | Sahu, S S | - |
| date.accessioned | 2010-02-22T06:18:57Z | - |
| date.available | 2010-02-22T06:18:57Z | - |
| date.issued | 2009 | - |
| identifier.citation | International Journal of Recent Trends in Engineering, Vol 2, No. 5, November 2009 | en |
| identifier.uri | http://hdl.handle.net/2080/1181 | - |
| description.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. | en |
| format.extent | 352326 bytes | - |
| format.mimetype | application/pdf | - |
| language.iso | en | - |
| subject | Genetic algorithms | en |
| subject | multiobjective optimization | en |
| subject | Pareto-optimal solutions | en |
| subject | global optimization | en |
| subject | Crowding distance | en |
| title | Optimal Weighting of Assets using a Multi-objective Evolutionary Algorithm | en |
| type | Article | en |
| Appears in Collections: | Journal Articles
|
Files in This Item:
| File |
Description |
Size | Format |
|---|
| sudhanshu2.pdf | | 344Kb | Adobe PDF | View/Open |
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