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Identifying common spectral and asymmetric features in stock returns

dc.contributor.authorCaiado, Jorge
dc.contributor.authorCrato, Nuno
dc.date.accessioned2023-05-09T14:09:31Z
dc.date.available2023-05-09T14:09:31Z
dc.date.issued2007
dc.description.abstractThis paper proposes spectral and asymmetric-volatility based methods for cluster analysis of stock returns. Using the information about both the periodogram of the squared returns and the estimated parameters in the TARCH equation, we compute a distance matrix for the stock returns. Clusters are formed by looking to the hierarchical structure tree (or dendrogram) and the computed principal coordinates. We employ these techniques to investigate the similarities and dissimilarities between the "blue-chip" stocks used to compute the Dow Jones Industrial Average (DJIA) index. For reference, we investigate also the similarities among stock returns by mean and squared correlation methods.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationCaiado, Jorge and Nuno Crato .(2007). “Identifying common spectral and asymmetric features in stock returns”. MPRA Paper No. 6607 -2007. (Search PDF in 2023).pt_PT
dc.identifier.doiMPRA Paper No. 6607/ 2007. (Search PDF in 2023).pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.5/27735
dc.language.isoengpt_PT
dc.publisherMPRA - Munich Personal RePEc Archivept_PT
dc.subjectAsymmetric Effectspt_PT
dc.subjectCluster Analysispt_PT
dc.subjectDJIA Stock Returnspt_PT
dc.subjectPeriodogrampt_PT
dc.subjectThreshold ARCH Modelpt_PT
dc.subjectVolatilitypt_PT
dc.titleIdentifying common spectral and asymmetric features in stock returnspt_PT
dc.typeworking paper
dspace.entity.typePublication
rcaap.rightsopenAccesspt_PT
rcaap.typeworkingPaperpt_PT

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