Optimal portfolio selection with stochastic maximum downside risk and uncertain implicit transaction costs

dc.contributor.authorMushori, Sabastine
dc.contributor.authorChikobvu, Delson
dc.date.accessioned2018-09-04T05:50:34Z
dc.date.available2018-09-04T05:50:34Z
dc.date.issued2017
dc.descriptionPublished Articleen_US
dc.description.abstractA multi-stage stochastic optimal portfolio policy that minimizes downside risk in the presence of uncertain implicit transaction costs is proposed. As asset returns in economic recessions and booms are characterised by extreme movements, some individual stocks show an extreme reaction while others exhibit a milder reaction. The study therefore considers a risk-averse and conservative investor who is highly concerned about the performance of his portfolio in an economic recession environment. Maximum negative deviation is taken as the downside risk and stochastic programming is applied with stochastic data given in the form of a scenario tree. A set of discrete scenarios of asset returns is considered, taking the deviation around each return scenario. Thus uncertainties of asset returns and implicit transaction costs are represented by discrete approximations of a multi-variate continuous distribution. The portfolio is rebalanced at discrete time intervals as new information on returns get realised. First-stage optimal-portfolio results show that implicit transaction costs vary from 7.1% to 16.7% of returns on investment.en_US
dc.format.extent411 079 bytes, 1 file
dc.format.mimetypeApplication/PDF
dc.identifier.issn1995-7076
dc.identifier.urihttp://hdl.handle.net/11462/1651
dc.language.isoen_USen_US
dc.publisherJournal of Economic and Financial Sciencesen_US
dc.relation.ispartofseriesVolume 10;Number 3
dc.subjectDiscrete scenariosen_US
dc.subjectImplicit transaction costsen_US
dc.subjectMaximum downside risken_US
dc.subjectUncertaintyen_US
dc.titleOptimal portfolio selection with stochastic maximum downside risk and uncertain implicit transaction costsen_US
dc.typeArticleen_US

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