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Tail index estimation in the presence of covariates

2023-08Artigo científico Acesso aberto
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dc.contributor.authorNicolau, João
dc.contributor.authorRodrigues, Paulo M.M.
dc.contributor.authorStoykov, Marian Z.
dc.contributor.institutionNOVA School of Business and Economics (NOVA SBE)
dc.contributor.pblElsevier Science Publisher B.V.
dc.date.accessioned2023-11-03T22:10:46Z
dc.date.available2023-11-03T22:10:46Z
dc.date.issued2023-08
dc.descriptionFunding Information: The authors thank two anonymous referees, an Associate Editor, and the Co-Editor (Torben Andersen) for their helpful and constructive feedback. Financial support from the Portuguese Foundation for Science and Technology (FCT) through projects CEMAPRE/REM - UIDB/05069/2020 , PTDC/EGE-ECO/28924/2017 , and ( UID/ECO/00124/2013 and Social Sciences DataLab, Project 22209 ), POR Lisboa ( LISBOA-01-0145-FEDER-007722 and Social Sciences DataLab, Project 22209 ) and POR Norte (Social Sciences DataLab, Project 22209 ) is also gratefully acknowledged. Publisher Copyright: © 2023 The Authors
dc.description.abstractThis paper provides novel theoretical results for the estimation of the conditional tail index of Pareto and Pareto-type distributions in a time series context. We show that both the estimators and relevant test statistics are normally distributed in the limit, when independent and identically distributed or dependent data are considered. Simulation results provide support for the theoretical findings and highlight the good finite sample properties of the approach in a time series context. The proposed methodology is then used to analyse stock returns’ tail risk dynamics. Two empirical applications are provided. The first consists in testing whether the time-varying tail exponents across firms follow Kelly and Jiang's (2014) assumption of common firm level tail dynamics. The results obtained from our sample seem not to favour this hypothesis. The second application, consists of the evaluation of the impact of two market risk indicators, VIX and Expected Shortfall (ES) and two firm specific covariates, capitalization and market-to-book on stocks tail risk dynamics. Although all variables seem important drivers of firms’ tail risk dynamics, it is found that ES and firms’ capitalization seem to have overall wider impact.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent19
dc.format.extent2124582
dc.identifier.doi10.1016/j.jeconom.2023.04.002
dc.identifier.issn0304-4076
dc.identifier.otherPURE: 65185606
dc.identifier.otherPURE UUID: e3a0deb1-f49e-4496-912d-1562e89da81a
dc.identifier.otherScopus: 85162028895
dc.identifier.urihttp://hdl.handle.net/10362/159528
dc.identifier.urlhttps://www.scopus.com/pages/publications/85162028895
dc.language.isoeng
dc.peerreviewedyes
dc.subjectCovariates information
dc.subjectExtreme value theory
dc.subjectPareto-type distributions
dc.subjectTail index
dc.subjectEconomics and Econometrics
dc.subjectApplied Mathematics
dc.titleTail index estimation in the presence of covariatesen
dc.title.subtitleStock returns’ tail risk dynamicsen
dc.typejournal article
degois.publication.firstPage2266
degois.publication.issue2
degois.publication.lastPage2284
degois.publication.titleJournal of Econometrics
degois.publication.volume235
dspace.entity.typePublication
rcaap.rightsopenAccess

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