Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.ejor.2012.03.012
DC FieldValue
dc.titlePortfolio value-at-risk optimization for asymmetrically distributed asset returns
dc.contributor.authorGoh, J.W.
dc.contributor.authorLim, K.G.
dc.contributor.authorSim, M.
dc.contributor.authorZhang, W.
dc.date.accessioned2013-10-09T06:18:10Z
dc.date.available2013-10-09T06:18:10Z
dc.date.issued2012
dc.identifier.citationGoh, J.W., Lim, K.G., Sim, M., Zhang, W. (2012). Portfolio value-at-risk optimization for asymmetrically distributed asset returns. European Journal of Operational Research 221 (2) : 397-406. ScholarBank@NUS Repository. https://doi.org/10.1016/j.ejor.2012.03.012
dc.identifier.issn03772217
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/44188
dc.description.abstractWe propose a new approach to portfolio optimization by separating asset return distributions into positive and negative half-spaces. The approach minimizes a newly-defined Partitioned Value-at-Risk (PVaR) risk measure by using half-space statistical information. Using simulated data, the PVaR approach always generates better risk-return tradeoffs in the optimal portfolios when compared to traditional Markowitz mean-variance approach. When using real financial data, our approach also outperforms the Markowitz approach in the risk-return tradeoff. Given that the PVaR measure is also a robust risk measure, our new approach can be very useful for optimal portfolio allocations when asset return distributions are asymmetrical. © 2012 Elsevier B.V. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.ejor.2012.03.012
dc.sourceScopus
dc.subjectAsymmetric distributions
dc.subjectPartitioned value-at-risk
dc.subjectPortfolio optimization
dc.subjectRisk management
dc.subjectRobust risk measures
dc.typeArticle
dc.contributor.departmentDECISION SCIENCES
dc.contributor.departmentFINANCE
dc.description.doi10.1016/j.ejor.2012.03.012
dc.description.sourcetitleEuropean Journal of Operational Research
dc.description.volume221
dc.description.issue2
dc.description.page397-406
dc.description.codenEJORD
dc.identifier.isiut000304849700013
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