Comparative Performance Evaluation of Multiobjective Optimization Algorithm For Portfolio Management

Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/1117

Full metadata record

DC Field	Value	Language
dc.contributor.author	Mishra, S K	-
dc.contributor.author	Panda, G	-
dc.contributor.author	Meher, S	-
dc.date.accessioned	2009-12-29T09:30:53Z	-
dc.date.available	2009-12-29T09:30:53Z	-
dc.date.issued	2009	-
dc.identifier.citation	International Symposium on Biologically Inspired Computing and Applications (BICA-2009), Bhubaneswar, India, December 21-22, 2009	en
dc.identifier.uri	http://hdl.handle.net/2080/1117	-
dc.description.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.	en
dc.format.extent	194016 bytes	-
dc.format.mimetype	application/pdf	-
dc.language.iso	en	-
dc.publisher	IEEE	en
dc.subject	Multi-objective optimization,	en
dc.subject	Multi-objective optimization,	en
dc.subject	Paretooptimal solutions,	en
dc.subject	Crowding distance,	en
dc.subject	global optimization,	en
dc.subject	Pareto front.	en
dc.title	Comparative Performance Evaluation of Multiobjective Optimization Algorithm For Portfolio Management	en
dc.type	Article	en
Appears in Collections:	Conference Papers

Files in This Item:

File	Description	Size	Format
Dspace BICA1.pdf		189.47 kB	Adobe PDF	View/Open

Show simple item record