Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/13899
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dc.contributor.authorRoman, D-
dc.contributor.authorArbex Valle, C-
dc.contributor.authorMitra, G-
dc.date.accessioned2017-01-19T15:08:20Z-
dc.date.available2017-01-19T15:08:20Z-
dc.date.issued2017-
dc.identifier.citationComputational Management Science, (2017)en_US
dc.identifier.issn1619-697X-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/13899-
dc.description.abstractIn the last decade, a few models of portfolio construction have been proposed which apply Second Order Stochastic Dominance (SSD) as a choice criterion. SSD approach requires the use of a reference distribution which acts as a benchmark. The return distribution of the computed portfolio dominates the benchmark by the SSD criterion. The benchmark distribution naturally plays an important role since di erent benchmarks lead to very di erent portfolio solutions. In this paper we describe a novel concept of reshaping the benchmark distribution with a view to obtaining portfolio solutions which have enhanced return distributions. The return distribution of the constructed portfolio is considered enhanced if the left tail is improved, the downside risk is reduced and the standard deviation remains within a speci ed range. We extend this approach from long only to long-short strategies which are used by many hedge fund and quant fund practitioners. We present computational results which illustrate (i) how this approach leads to superior portfolio performance (ii) how signi cantly better performance is achieved for portfolios that include shorting of assets.en_US
dc.language.isoenen_US
dc.publisherSpringer Verlagen_US
dc.subjectPortfolio optimisationen_US
dc.subjectStochastic dominanceen_US
dc.subjectReference distributionen_US
dc.subjectLeft tailen_US
dc.subjectDownside risken_US
dc.titleNovel approaches for portfolio construction using second order stochastic dominanceen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.1007/s10287-017-0274-9-
dc.relation.isPartOfComputational Management Science-
pubs.publication-statusAccepted-
Appears in Collections:Dept of Mathematics Research Papers

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