Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.advisorMitra, G-
dc.contributor.authorGuertler, Marion-
dc.descriptionThis thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 16/01/2004.en_US
dc.description.abstractIn this thesis modelling and solution methods for portfolio optimisation are presented. The investigations reported in this thesis extend the Markowitz mean-variance model to the domain of quadratic mixed integer programming (QMIP) models which are 'NP-hard' discrete optimisation problems. In addition to the modelling extensions a number of challenging aspects of solution algorithms are considered. The relative performances of sparse simplex (SSX) as well as the interior point method (IPM) are studied in detail. In particular, the roles of 'warmstart' and dual simplex are highlighted as applied to the construction of the efficient frontier which requires processing a family of problems; that is, the portfolio planning model stated in a parametric form. The method of solving QMIP models using the branch and bound algorithm is first developed; this is followed up by heuristics which improve the performance of the (discrete) solution algorithm. Some properties of the efficient frontier with discrete constraints are considered and a method of computing the discrete efficient frontier (DEF) efficiently is proposed. The computational investigation considers the efficiency and effectiveness in respect of the scale up properties of the proposed algorithm. The extensions of the real world models and the proposed solution algorithms make contribution as new knowledge.en_US
dc.publisherBrunel University, School of Information Systems, Computing and Mathematics-
dc.relation.ispartofSchool of Information Systems, Computing and Mathematics-
dc.subjectQuadratic mixed integer programming (QIMP)en_US
dc.subjectSparse simplex (SSX)en_US
dc.subjectInterior point method (IPM)en_US
dc.subjectDiscrete efficient frontier (DEF)en_US
dc.titleModelling and solution methods for portfolio optimisationen_US
Appears in Collections:Dept of Mathematics Theses
Mathematical Sciences

Files in This Item:
File Description SizeFormat 
FulltextThesis.pdf4.27 MBAdobe PDFView/Open

Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.