Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/1117
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dc.contributor.authorMishra, S K-
dc.contributor.authorPanda, G-
dc.contributor.authorMeher, S-
dc.date.accessioned2009-12-29T09:30:53Z-
dc.date.available2009-12-29T09:30:53Z-
dc.date.issued2009-
dc.identifier.citationInternational Symposium on Biologically Inspired Computing and Applications (BICA-2009), Bhubaneswar, India, December 21-22, 2009en
dc.identifier.urihttp://hdl.handle.net/2080/1117-
dc.description.abstractThe moto of portfolio optimization is to find an optimal set of assets to invest on, as well as the optimal investment for each asset. This optimal selection and weighting of assets is a multi-objective problem where total profit of investment has to be maximized and total risk is to be minimized. In this paper the Portfolio optimization is solved using three different multi-objective algorithms and their performance have been compared in terms of pareto fronts, the delta, C and S metrics. Exhaustive simulation study of various portfolios clearly demonstrates the superior portfolio management capability of NSGA II based method compared to other two methods.en
dc.format.extent194016 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen-
dc.publisherIEEEen
dc.subjectMulti-objective optimization,en
dc.subjectMulti-objective optimization,en
dc.subjectParetooptimal solutions,en
dc.subjectCrowding distance,en
dc.subjectglobal optimization,en
dc.subjectPareto front.en
dc.titleComparative Performance Evaluation of Multiobjective Optimization Algorithm For Portfolio Managementen
dc.typeArticleen
Appears in Collections:Conference Papers

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