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dc.contributor.advisorSubasi, Munevver Mine
dc.contributor.authorAlreshidi, Nasser Aedh
dc.date.accessioned2019-09-25T13:51:50Z
dc.date.available2019-09-25T13:51:50Z
dc.date.created2019-05
dc.date.issued2019-05
dc.date.submittedMay 2019
dc.identifier.urihttp://hdl.handle.net/11141/2921
dc.descriptionThesis (Ph.D.) - Florida Institute of Technology, 2019en_US
dc.description.abstractWe consider a two-stage stochastic bond portfolio optimization problem, where an investor aims to optimize the cost of bond portfolio under different scenarios while ensuring predefined liabilities during a given planning horizon. The investor needs to optimally decide whether to buy, hold, or sell bonds based upon present market conditions under different scenarios and varying assumptions, where the scenarios are determined based on interest rates and buying prices of the bonds. Three stochastic integer programming models are proposed and applied to real-data from Saudi Sukuk (Bond) Market. The case-study results demonstrate the varying optimal decisions made to manage bond portfolio over the two stages. In addition, the three stochastic programming models for bond portfolio optimization, are tested on a large set of randomly generated instances similar to the Saudi Sukuk (Bond) Market. The results of computational experiments attest the efficiency of the proposed models.en_US
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen_US
dc.rightsCC BY 4.0en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/legalcodeen_US
dc.titleTwo-Stage Mixed Integer Stochastic Programming and Its Application to Bond Portfolio Optimizationen_US
dc.typeDissertationen_US
dc.date.updated2019-07-01T15:36:39Z
thesis.degree.nameDoctorate of Philosophy in Operation Researchen_US
thesis.degree.levelDoctoralen_US
thesis.degree.disciplineOperations Researchen_US
thesis.degree.departmentMathematical Sciencesen_US
thesis.degree.grantorFlorida Institute of Technologyen_US
dc.type.materialtext


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