Comparative performance evaluation of multiobjective optimization algorithms for portfolio management

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dc.contributor.authorMishra S.K.en_US
dc.contributor.authorMeher S.en_US
dc.contributor.authorPanda G.en_US
dc.contributor.authorPanda A.en_US
dc.date.accessioned2025-02-11T12:19:33Z
dc.date.issued2009
dc.description.abstractThe objective of portfolio optimization is to find an optimal set of assets to invest onen_US
dc.description.abstractas well as to determine 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 problem is solved using three different multi-objective algorithms and their performance have been compared in terms of Pareto frontsen_US
dc.description.abstractthe deltaen_US
dc.description.abstractC and S metrics. Exhaustive simulation study of various portfolios clearly demonstrates the superior portfolio management capability of non-dominated sorting genetic algorithm II (NSGA II) based method compared to other two methods. �2009 IEEE.en_US
dc.identifier.urihttp://dx.doi.org/10.1109/NABIC.2009.5393739
dc.identifier.urihttps://idr.iitbbs.ac.in/handle/2008/19
dc.language.isoenen_US
dc.subjectCrowding distanceen_US
dc.subjectMulti-objective optimizationen_US
dc.subjectPareto fronten_US
dc.subjectPareto-optimal solutionsen_US
dc.titleComparative performance evaluation of multiobjective optimization algorithms for portfolio managementen_US
dc.typeConference Paperen_US

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