Show simple item record

dc.contributor.authorHan, Heejoonen
dc.contributor.authorLinton, Oliveren
dc.contributor.authorOka, Tatsushien
dc.contributor.authorWhang, Yoon-Jaeen
dc.date.accessioned2016-06-07T12:25:04Z
dc.date.available2016-06-07T12:25:04Z
dc.date.issued2016-03-30en
dc.identifier.issn0304-4076
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/256194
dc.description.abstractThis paper proposes the cross-quantilogram to measure the quantile dependence between two time series. We apply it to test the hypothesis that one time series has no directional predictability to another time series. We establish the asymptotic distribution of the cross-quantilogram and the corresponding test statistic. The limiting distributions depend on nuisance parameters. To construct consistent confidence intervals we employ a stationary bootstrap procedure; we establish consistency of this bootstrap. Also, we consider a self-normalized approach, which yields an asymptotically pivotal statistic under the null hypothesis of no predictability. We provide simulation studies and two empirical applications. First, we use the cross-quantilogram to detect predictability from stock variance to excess stock return. Compared to existing tools used in the literature of stock return predictability, our method provides a more complete relationship between a predictor and stock return. Second, we investigate the systemic risk of individual financial institutions, such as JP Morgan Chase, Morgan Stanley and AIG.
dc.description.sponsorshipCambridge INET
dc.languageEnglishen
dc.language.isoenen
dc.publisherElsevier
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectquantileen
dc.subjectcorrelogramen
dc.subjectdependenceen
dc.subjectpredictabilityen
dc.subjectsystemic risken
dc.titleThe cross-quantilogram: Measuring quantile dependence and testing directional predictability between time seriesen
dc.typeArticle
dc.description.versionThis is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.jeconom.2016.03.001en
prism.endingPage270
prism.publicationDate2016en
prism.publicationNameThe Journal of Econometricsen
prism.startingPage251
prism.volume193en
dc.identifier.doi10.17863/CAM.136
dcterms.dateAccepted2016-03-13en
rioxxterms.funderNational Research Foundation of Koreaen
rioxxterms.funderEuropean Research Councilen
rioxxterms.funderNational Research Foundation of Koreaen
rioxxterms.identifier.projectNRF-2013S1A5A8021502en
rioxxterms.identifier.projectNAMSEFen
rioxxterms.identifier.projectNRF-2011-342-B00004en
rioxxterms.versionofrecord10.1016/j.jeconom.2016.03.001en
rioxxterms.versionAMen
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en
rioxxterms.licenseref.startdate2016-03-30en
dc.contributor.orcidLinton, Oliver [0000-0003-2313-0564]
dc.identifier.eissn1872-6895
rioxxterms.typeJournal Article/Reviewen
rioxxterms.funder.project86c3905c-f2ed-46e3-961a-c484b53fb28den
rioxxterms.funder.project5ec6fa14-6ead-4f3e-b942-9fdfb560aa6aen
rioxxterms.funder.project92b88e7b-2256-40d5-95e8-be35e6b075dden
rioxxterms.freetoread.startdate2018-03-30


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivatives 4.0 International
Except where otherwise noted, this item's licence is described as Attribution-NonCommercial-NoDerivatives 4.0 International