Mutual information: a measure of dependency for nonlinear time series

dc.contributor.authorDionísio, Andreia
dc.contributor.authorMenezes, Rui
dc.contributor.authorMendes, Diana
dc.date.accessioned2009-11-16T15:55:47Z
dc.date.available2009-11-16T15:55:47Z
dc.date.issued2004
dc.description.abstractThe main goal of the paper is to show how mutual information can be used as a measure of dependence in financial time series. One major advantage of this approach resides precisely in its ability to account for nonlinear dependencies with no need to specify a theoretical probability distribution or use of a mean-variance model.en
dc.format.extent130345 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.accesstypelivreen
dc.identifier.authoremailandreia@uevora.pt
dc.identifier.authoremailrui.menezes@iscte.pt
dc.identifier.authoremaildiana.mendes@iscte.pt
dc.identifier.pagina326-329en
dc.identifier.revistaPhysica Aen
dc.identifier.scientificarea637en
dc.identifier.urihttp://hdl.handle.net/10174/1818
dc.identifier.volume344en
dc.language.isoeng
dc.peerreviewedyesen
dc.publisherElsevieren
dc.rightsopenAccessen
dc.subjectMutual information; Nonlinear dependence; Efficient market hypothesisen
dc.titleMutual information: a measure of dependency for nonlinear time seriesen
dc.typearticleen

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