Mean-Variance Portfolio Selection with the Ordered Weighted Average

Laengle, S; Loyola, G; Merigó, JM

Mean-Variance Portfolio Selection with the Ordered Weighted Average

Laengle, S Loyola, G Merigó, JM

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Fuzzy Systems, 2017, 25 (2), pp. 350 - 362
Issue Date:: 2017-04-01

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Field	Value	Language
dc.contributor.author	Laengle, S	en_US
dc.contributor.author	Loyola, G	en_US
dc.contributor.author	Merigó, JM https://orcid.org/0000-0002-4672-6961	en_US
dc.date.issued	2017-04-01	en_US
dc.identifier.citation	IEEE Transactions on Fuzzy Systems, 2017, 25 (2), pp. 350 - 362	en_US
dc.identifier.issn	1063-6706	en_US
dc.identifier.uri	http://hdl.handle.net/10453/126404
dc.description.abstract	© 1993-2012 IEEE. Portfolio selection is the theory that studies the process of selecting the optimal proportion of different assets. The first approach was introduced by Harry Markowitz and was based on a mean-variance framework. This paper introduces the ordered weighted average (OWA) in the mean-variance model. The main idea is to replace the classical mean and variance by the OWA operator. By doing so, the new model is able to study different degrees of optimism and pessimism in the analysis being able to develop an approach that considers the decision makers attitude in the selection process. This paper also suggests a new framework for dealing with the attitudinal character of the decision maker based on the numerical values of the available arguments. The main advantage of this method is the ability to adapt to many situations offering a more complete representation of the available data from the most pessimistic situation to the most optimistic one. An illustrative with fictitious data and a real example are studied.	en_US
dc.relation.ispartof	IEEE Transactions on Fuzzy Systems	en_US
dc.relation.isbasedon	10.1109/TFUZZ.2016.2578345	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Mean-Variance Portfolio Selection with the Ordered Weighted Average	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	25	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	0102 Applied Mathematics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
utslib.copyright.status	closed_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	25	en_US

Abstract:

© 1993-2012 IEEE. Portfolio selection is the theory that studies the process of selecting the optimal proportion of different assets. The first approach was introduced by Harry Markowitz and was based on a mean-variance framework. This paper introduces the ordered weighted average (OWA) in the mean-variance model. The main idea is to replace the classical mean and variance by the OWA operator. By doing so, the new model is able to study different degrees of optimism and pessimism in the analysis being able to develop an approach that considers the decision makers attitude in the selection process. This paper also suggests a new framework for dealing with the attitudinal character of the decision maker based on the numerical values of the available arguments. The main advantage of this method is the ability to adapt to many situations offering a more complete representation of the available data from the most pessimistic situation to the most optimistic one. An illustrative with fictitious data and a real example are studied.

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http://hdl.handle.net/10453/126404