Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/9639
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dc.contributor.authorRoman, D-
dc.contributor.authorMitra, G-
dc.contributor.authorZverovich, V-
dc.date.accessioned2014-12-23T15:21:00Z-
dc.date.available2013-07-01-
dc.date.available2014-12-23T15:21:00Z-
dc.date.issued2013-
dc.identifier.citationEuropean Journal of Operational Research, 228: 1, pp. 273 - 281, 2013en_US
dc.identifier.issn0377-2217-
dc.identifier.urihttp://www.sciencedirect.com/science/article/pii/S0377221713000829-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/9639-
dc.description.abstractSecond order Stochastic Dominance (SSD) has a well recognised importance in portfolio selection, since it provides a natural interpretation of the theory of risk-Averse investor behaviour. Recently, SSD-based models of portfolio choice have been proposed; these assume that a reference distribution is available and a portfolio is constructed, whose return distribution dominates the reference distribution with respect to SSD. We present an empirical study which analyses the effectiveness of such strategies in the context of enhanced indexation. Several datasets, drawn from FTSE 100, SP 500 and Nikkei 225 are investigated through portfolio rebalancing and backtesting. Three main conclusions are drawn. First, the portfolios chosen by the SSD based models consistently outperformed the indices and the traditional index trackers. Secondly, the SSD based models do not require imposition of cardinality constraints since naturally a small number of stocks are selected. Thus, they do not present the computational difficulty normally associated with index tracking models. Finally, the SSD based models are robust with respect to small changes in the scenario set and little or no rebalancing is necessary. In this paper we present a unified framework which incorporates (a) SSD, (b) downside risk (Conditional Value-At-Risk) minimisation and (c) enhanced indexation. © 2013 Elsevier B.V. All rights reserved.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectFinanceen_US
dc.subjectPortfolio choiceen_US
dc.subjectIndex trackingen_US
dc.subjectMean-risken_US
dc.subjectStochastic dominanceen_US
dc.titleEnhanced indexation based on second-order stochastic dominanceen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.1016/j.ejor.2013.01.035-
dc.relation.isPartOfEuropean Journal of Operational Research-
dc.relation.isPartOfEuropean Journal of Operational Research-
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pubs.organisational-data/Brunel/Brunel Staff by College/Department/Division-
pubs.organisational-data/Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences-
pubs.organisational-data/Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences/Dept of Mathematics-
pubs.organisational-data/Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences/Dept of Mathematics/Mathematical Sciences-
pubs.organisational-data/Brunel/University Research Centres and Groups-
pubs.organisational-data/Brunel/University Research Centres and Groups/Brunel Business School - URCs and Groups-
pubs.organisational-data/Brunel/University Research Centres and Groups/Brunel Business School - URCs and Groups/Centre for Research into Entrepreneurship, International Business and Innovation in Emerging Markets-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Brunel Institute for Ageing Studies-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Brunel Institute of Cancer Genetics and Pharmacogenomics-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Centre for Systems and Synthetic Biology-
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