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Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/1333

Title: Application of Multi-Objective Evolutionary Algorithms in Computational Finance
Authors: Mishra, S K
Panda, G
Meher, S
Majhi, R
Keywords: Multi-objective optimization problem
Pareto-optimal solutions
Pareto Front
Global optimization
Non-dominated shorting
Issue Date: Dec-2010
Citation: National Conference on Convergence of Management Practices, 17-18th December, 2010, National Institute of Technology Warangal (NITW), India.
Abstract: Application of Multiobjective evolutionary algorithms (MOEAs) in diversified domains has gained popularity in wide area ranging from engineering and computer science to ecology, sociology and medicine field. From these diversified application areas of evolutionary algorithms, computational finance constitutes a very promising field. The use of evolutionary algorithms for solving multi-objective optimization problem emerges as a potential field of research in recent years. This paper deals with application of MOEAs for different problems in computational finance. Different applications are explained briefly and exhaustive simulation study has been carried out for one particular application i.e. investment portfolio optimization. In this paper the Portfolio optimization is solved using two different multi-objective algorithms SPEA2 and NSGA-II. Their performances have been compared in terms of Pareto fronts, the delta, and C and S metrics.
Description: Copyright belongs to Proceedings Publisher
URI: http://hdl.handle.net/2080/1333
Appears in Collections:Conference Papers

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