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Index tracking optimization with cardinality constraint: a performance comparison of genetic algorithms and tabu search heuristics

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Index tracking optimization with cardinality constraint: a performance comparison of genetic algorithms and tabu search heuristics

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dc.contributor.author García García, Fernando es_ES
dc.contributor.author Guijarro, Francisco es_ES
dc.contributor.author Oliver-Muncharaz, Javier es_ES
dc.date.accessioned 2019-06-07T20:02:29Z
dc.date.available 2019-06-07T20:02:29Z
dc.date.issued 2018 es_ES
dc.identifier.issn 0941-0643 es_ES
dc.identifier.uri http://hdl.handle.net/10251/121737
dc.description.abstract [EN] The aim of this study was to compare the performance of the well-known genetic algorithms and tabu search heuristics with the financial problem of the partial tracking of a stock market index. Although the weights of each stock in a tracking portfolio can be efficiently determined by means of quadratic programming, identifying the appropriate stocks to include in the portfolio is an NP-hard problem which can only be addressed by heuristics. Seven real-world indexes were used to compare the above techniques, and results were obtained for different tracking portfolio cardinalities. The results show that tabu search performs more efficiently with both real and artificial indexes. In general, the tracking portfolios obtained performed well in both in-sample and out-of-sample periods, so that these heuristics can be considered as appropriate solutions to the problem of tracking an index by means of a small subset of stocks. es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Neural Computing and Applications es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Index tracking es_ES
dc.subject Heuristics es_ES
dc.subject S&P 500 es_ES
dc.subject Artificial index es_ES
dc.subject.classification ECONOMIA FINANCIERA Y CONTABILIDAD es_ES
dc.title Index tracking optimization with cardinality constraint: a performance comparison of genetic algorithms and tabu search heuristics es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s00521-017-2882-2 es_ES
dc.rights.accessRights Abierto es_ES
dc.date.embargoEndDate 2019-10-01 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 García García, F.; Guijarro, F.; Oliver-Muncharaz, J. (2018). Index tracking optimization with cardinality constraint: a performance comparison of genetic algorithms and tabu search heuristics. Neural Computing and Applications. 30(8):2625-2641. https://doi.org/10.1007/s00521-017-2882-2 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://doi.org/10.1007/s00521-017-2882-2 es_ES
dc.description.upvformatpinicio 2625 es_ES
dc.description.upvformatpfin 2641 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 30 es_ES
dc.description.issue 8 es_ES
dc.relation.pasarela S\367719 es_ES
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