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Dynamic generation of investment recommendations using grammatical evolution

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Computación Evolutiva y Redes Neuronales (EVANNAI)es
dc.contributor.authorMartín Fernández, Carlos
dc.contributor.authorQuintana, David
dc.contributor.authorIsasi, Pedro
dc.contributor.funderComunidad de Madrides
dc.contributor.funderUniversidad Carlos III de Madrides
dc.date.accessioned2022-04-04T10:33:24Z
dc.date.available2022-04-04T10:33:24Z
dc.date.issued2021-04-22
dc.description.abstractThe attainment of trading rules using Grammatical Evolution traditionally follows a static approach. A single rule is obtained and then used to generate investment recommendations over time. The main disadvantage of this approach is that it does not consider the need to adapt to the structural changes that are often associated with financial time series. We improve the canonical approach introducing an alternative that involves a dynamic selection mechanism that switches between an active rule and a candidate one optimized for the most recent market data available. The proposed solution seeks the flexibility required by structural changes while limiting the transaction costs commonly associated with constant model updates. The performance of the algorithm is compared with four alternatives: the standard static approach; a sliding window-based generation of trading rules that are used for a single time period, and two ensemble-based strategies. The experimental results, based on market data, show that the suggested approach beats the rest.en
dc.description.sponsorshipThe authors would like to acknowledge the financial support of the Spanish Ministry of Science, Innovation and Universities under grant PGC2018-096849-B-I00 (MCFin). This work has been supported by the Madrid Government (Comunidad de Madrid-Spain) under the Multiannual Agreement with UC3M in the line of Excellence of University Professors (EPUC3MXX), and in the context of the V PRICIT (Regional Programme of Research and Technological Innovation).en
dc.identifier.bibliographicCitationMartín, C., Quintana, D., & Isasi, P. (2021). Dynamic Generation of Investment Recommendations Using Grammatical Evolution. International Journal Of Interactive Multimedia And Artificial Intelligence, 6(Regular Issue), 104-111. http://doi.org/10.9781/ijimai.2021.04.007en
dc.identifier.doihttps://doi.org/10.9781/ijimai.2021.04.007
dc.identifier.issn1989-1660
dc.identifier.publicationfirstpage104
dc.identifier.publicationissue6
dc.identifier.publicationlastpage111
dc.identifier.publicationtitleInternational Journal of Interactive Multimedia and Artificial Intelligenceen
dc.identifier.publicationvolume6
dc.identifier.urihttps://hdl.handle.net/10016/34521
dc.identifier.uxxiAR/0000028968
dc.language.isoeng
dc.publisherUniversidad Internacional de la Rioja (UNIR)en
dc.relation.projectIDGobierno de España. PGC2018-096849-B-I00en
dc.rights© UNIR, 2021
dc.rightsAtribución 3.0 España
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.subject.ecienciaInformáticaes
dc.subject.otherdynamic strategyen
dc.subject.otherevolutionaryen
dc.subject.othercomputationen
dc.subject.otherfinanceen
dc.subject.othergrammatical evolutionen
dc.subject.otherstructural changeen
dc.subject.othertradingen
dc.titleDynamic generation of investment recommendations using grammatical evolutionen
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
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