An Exact Algorithm for Small-Cardinality Constrained Portfolio Optimisation
dc.contributor.author | Graham, David | |
dc.contributor.author | Craven, Matthew | |
dc.date.accessioned | 2020-01-13T18:22:10Z | |
dc.date.issued | 2020-02-13 | |
dc.identifier.issn | 0160-5682 | |
dc.identifier.issn | 1476-9360 | |
dc.identifier.uri | http://hdl.handle.net/10026.1/15298 | |
dc.description.abstract |
Real-world portfolio optimisation problems are often NP-hard, their efficient frontiers (EFs) in practice being calculated by randomised algorithms. In this work, a deterministic method of decomposition of EFs into a short sequence of sub-EFs is presented. These sub-EFs may be calculated by a quadratic programming algorithm, the collection of such sub-EFs then being subjected to a sifting process to produce the full EF. Full EFs of portfolio optimisation problems with small cardinality constraints are computed to a high resolution, providing a fast and practical alternative to randomised algorithms. The method may also be used with other practical classes of portfolio problems, complete with differing measures of risk. Finally, it is shown that the identified sub-EFs correspond closely to local optima of the objective function of a case study evolutionary algorithm. | |
dc.format.extent | 1-17 | |
dc.language | en | |
dc.language.iso | en | |
dc.publisher | Taylor & Francis | |
dc.subject | portfolio selection | |
dc.subject | cardinality constraint | |
dc.subject | deterministic methods | |
dc.subject | evolutionary algorithm | |
dc.subject | operational research | |
dc.subject | quadratic programming | |
dc.title | An Exact Algorithm for Small-Cardinality Constrained Portfolio Optimisation | |
dc.type | journal-article | |
dc.type | Journal Article | |
plymouth.author-url | https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000513982300001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008 | |
plymouth.issue | 6 | |
plymouth.volume | 72 | |
plymouth.publication-status | Published online | |
plymouth.journal | Journal of the Operational Research Society | |
dc.identifier.doi | 10.1080/01605682.2020.1718019 | |
plymouth.organisational-group | /Plymouth | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA/EXTENDED UoA 10 - Mathematical Sciences | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA/EXTENDED UoA 10 - Mathematical Sciences/UoA 10 - Former and non-independent | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA/UoA10 Mathematical Sciences | |
plymouth.organisational-group | /Plymouth/Research Groups | |
plymouth.organisational-group | /Plymouth/Research Groups/Marine Institute | |
plymouth.organisational-group | /Plymouth/Users by role | |
plymouth.organisational-group | /Plymouth/Users by role/Academics | |
dcterms.dateAccepted | 2020-01-12 | |
dc.rights.embargodate | 2021-2-12 | |
dc.identifier.eissn | 1476-9360 | |
dc.rights.embargoperiod | Not known | |
rioxxterms.version | Accepted Manuscript | |
rioxxterms.versionofrecord | 10.1080/01605682.2020.1718019 | |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | |
rioxxterms.licenseref.startdate | 2020-02-13 | |
rioxxterms.type | Journal Article/Review |