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A surrogate similarity measure for the mean-variance frontier optimization problem under bound and cardinality constraints

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A surrogate similarity measure for the mean-variance frontier optimization problem under bound and cardinality constraints

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dc.contributor.author Guijarro, Francisco es_ES
dc.contributor.author Tsinaslanidis, Prodromos E. es_ES
dc.date.accessioned 2021-04-01T03:31:36Z
dc.date.available 2021-04-01T03:31:36Z
dc.date.issued 2021-03 es_ES
dc.identifier.issn 0160-5682 es_ES
dc.identifier.uri http://hdl.handle.net/10251/164819
dc.description.abstract [EN] This article deals with the mean-variance optimisation frontier problem when realistic constraints are considered. Our proposed methodology hybridises a heuristic algorithm with an exact solution approach. A genetic algorithm is applied for the identification of the assets in the portfolio, whilst the asset weights in the portfolios are obtained by a quadratic programming model. The proposed algorithmic framework produces a constrained frontier that actually fulfils the bound and cardinality constraints, unlike other proposals where the frontier is composed of several subfrontiers, each one considering the cardinality constraint but with different assets in each sub-frontier, thus violating the cardinality constraint. This brings us to propose a surrogate similarity measure for the optimisation of the constrained frontier, which differs from a previous proposal where no bound constraints were considered. es_ES
dc.language Inglés es_ES
dc.publisher Nature Publishing Group - Macmillan Publishers es_ES
dc.relation.ispartof Journal of the Operational Research Society es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Portfolio optimisation es_ES
dc.subject Cardinality constraint es_ES
dc.subject Bound constraint es_ES
dc.subject Genetic algorithm es_ES
dc.subject.classification ECONOMIA FINANCIERA Y CONTABILIDAD es_ES
dc.title A surrogate similarity measure for the mean-variance frontier optimization problem under bound and cardinality constraints es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1080/01605682.2019.1657367 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Economía y Ciencias Sociales - Departament d'Economia i Ciències Socials es_ES
dc.description.bibliographicCitation Guijarro, F.; Tsinaslanidis, PE. (2021). A surrogate similarity measure for the mean-variance frontier optimization problem under bound and cardinality constraints. Journal of the Operational Research Society. 72(3):564-579. https://doi.org/10.1080/01605682.2019.1657367 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1080/01605682.2019.1657367 es_ES
dc.description.upvformatpinicio 564 es_ES
dc.description.upvformatpfin 579 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 72 es_ES
dc.description.issue 3 es_ES
dc.relation.pasarela S\392223 es_ES
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