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Estimating returns and condicional volatility: a comparison between the ARMA-GARCH-M Models and the Backpropagation Neural Network

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Estimating returns and condicional volatility: a comparison between the ARMA-GARCH-M Models and the Backpropagation Neural Network

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dc.contributor.author García García, Fernando es_ES
dc.contributor.author Guijarro Martínez, Francisco es_ES
dc.contributor.author Moya Clemente, Ismael es_ES
dc.contributor.author Oliver Muncharaz, Javier es_ES
dc.date.accessioned 2016-01-18T16:04:31Z
dc.date.available 2016-01-18T16:04:31Z
dc.date.issued 2012-12
dc.identifier.issn 2174-6036
dc.identifier.uri http://hdl.handle.net/10251/60000
dc.description Creative Commons: Reconocimiento 3.0 España (CC BY 3.0 ES) es_ES
dc.description.abstract Econometric models have usually estimated both returns and conditional volatility in financial assets. This paper is intended in the comparison of this traditional approach with the more recent Backpropagation neural network. When applied to the Spanish Ibex-35 stock market index, we find that the neural network achieved significantly better performance in predicting conditional volatility, but similar results when predicting financial returns. es_ES
dc.language Inglés es_ES
dc.publisher Interlude es_ES
dc.relation.ispartof International Journal of Complex Systems in Science es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Conditional volatility es_ES
dc.subject Backpropagation neural network es_ES
dc.subject GARCH-M es_ES
dc.subject.classification ECONOMIA FINANCIERA Y CONTABILIDAD es_ES
dc.title Estimating returns and condicional volatility: a comparison between the ARMA-GARCH-M Models and the Backpropagation Neural Network es_ES
dc.type Artículo 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 García García, F.; Guijarro Martínez, F.; Moya Clemente, I.; Oliver Muncharaz, J. (2012). Estimating returns and condicional volatility: a comparison between the ARMA-GARCH-M Models and the Backpropagation Neural Network. International Journal of Complex Systems in Science. 2(1):21-26. http://hdl.handle.net/10251/60000 es_ES
dc.description.accrualMethod Senia es_ES
dc.relation.publisherversion http://www.ij-css.org/vol_02-01.html es_ES
dc.description.upvformatpinicio 21 es_ES
dc.description.upvformatpfin 26 es_ES
dc.type.version info:eu repo/semantics/publishedVersion es_ES
dc.description.volume 2 es_ES
dc.description.issue 1 es_ES
dc.relation.senia 232040 es_ES


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