- -

Algorithmic Trading Systems Based on Google Trends

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Algorithmic Trading Systems Based on Google Trends

Mostrar el registro sencillo del ítem

Ficheros en el ítem

Thumbnail
Nombre: 8295-23253-1-PB.pdf
Tamaño: 1.081Mb
Formato: PDF
Descripción: Versión editorial
Abrir
dc.contributor.author Gómez Martínez, Raúl es_ES
dc.contributor.author Prado Román, Camilo es_ES
dc.contributor.author De la Orden de la Cruz, María del Carmen es_ES
dc.date.accessioned 2018-11-06T07:52:10Z
dc.date.available 2018-11-06T07:52:10Z
dc.date.issued 2018-09-07
dc.identifier.isbn 9788490486894
dc.identifier.uri http://hdl.handle.net/10251/111930
dc.description.abstract [EN] In this paper we analyze five big data algorithmic trading systems based on artificial intelligence models that uses as predictors stats from Google Trends of dozens of financial terms. The systems were trained using monthly data from 2004 to 2017 and have been tested in a prospective way from January 2017 to February 2018. The performance of this systems shows that Google Trends is a good metric for global Investors’ Mood. Systems for Ibex and Eurostoxx are not profitable but Dow Jones, S&P 500 and Nasdaq systems has been profitable using long and short positions during the period studied. This evidence opens a new field for the investigation of trading systems based on big data instead of Chartism. es_ES
dc.format.extent 8 es_ES
dc.language Inglés es_ES
dc.publisher Editorial Universitat Politècnica de València es_ES
dc.relation.ispartof 2nd International Conference on Advanced Reserach Methods and Analytics (CARMA 2018) es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Web data es_ES
dc.subject Internet data es_ES
dc.subject Big data es_ES
dc.subject QCA es_ES
dc.subject PLS es_ES
dc.subject SEM es_ES
dc.subject Conference es_ES
dc.subject Behavioral finance es_ES
dc.subject Investors' mood es_ES
dc.subject Artificial Intelligence es_ES
dc.subject Bayesian network es_ES
dc.subject Google trends es_ES
dc.title Algorithmic Trading Systems Based on Google Trends es_ES
dc.type Capítulo de libro es_ES
dc.type Comunicación en congreso es_ES
dc.identifier.doi 10.4995/CARMA2018.2018.8295
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Gómez Martínez, R.; Prado Román, C.; De La Orden De La Cruz, MDC. (2018). Algorithmic Trading Systems Based on Google Trends. En 2nd International Conference on Advanced Reserach Methods and Analytics (CARMA 2018). Editorial Universitat Politècnica de València. 11-18. https://doi.org/10.4995/CARMA2018.2018.8295 es_ES
dc.description.accrualMethod OCS es_ES
dc.relation.conferencename CARMA 2018 - 2nd International Conference on Advanced Research Methods and Analytics es_ES
dc.relation.conferencedate Julio 12-13,2018 es_ES
dc.relation.conferenceplace Valencia, Spain es_ES
dc.relation.publisherversion http://ocs.editorial.upv.es/index.php/CARMA/CARMA2018/paper/view/8295 es_ES
dc.description.upvformatpinicio 11 es_ES
dc.description.upvformatpfin 18 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela OCS\8295 es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem