Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/1117
Title: Comparative Performance Evaluation of Multiobjective Optimization Algorithm For Portfolio Management
Authors: Mishra, S K
Panda, G
Meher, S
Keywords: Multi-objective optimization,
Multi-objective optimization,
Paretooptimal solutions,
Crowding distance,
global optimization,
Pareto front.
Issue Date: 2009
Publisher: IEEE
Citation: International Symposium on Biologically Inspired Computing and Applications (BICA-2009), Bhubaneswar, India, December 21-22, 2009
Abstract: The 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.
URI: http://hdl.handle.net/2080/1117
Appears in Collections:Conference Papers

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