Time-varying autoregressive conditional duration model

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dc.contributor.authorADRIANA BRUSCATO BORTOLUZZO
dc.contributor.authorMorettin, Pedro A.
dc.contributor.authorToloi, Clelia MC T.
dc.coverage.paisNão Informadopt_BR
dc.creatorMorettin, Pedro A.
dc.creatorToloi, Clelia MC T.
dc.date.accessioned2022-10-08T18:31:05Z
dc.date.available2022-10-08T18:31:05Z
dc.date.issued2010
dc.description.otherThe main goal of this work is to generalize the autoregressive conditional duration (ACD) model applied to times between trades to the case of time-varying parameters. The use of wavelets allows that parameters vary through time and makes possible the modeling of non-stationary processes without preliminary data transformations. The time-varying ACD model estimation was done by maximum-likelihood with standard exponential distributed errors. The properties of the estimators were assessed via bootstrap. We present a simulation exercise for a non-stationary process and an empirical application to a real series, namely the TELEMAR stock. Diagnostic and goodness of fit analysis suggest that the time-varying ACD model simultaneously modeled the dependence between durations, intra-day seasonality and volatility.pt_BR
dc.format.extent847 - 864pt_BR
dc.format.mediumDigitalpt_BR
dc.identifier.doihttps://doi.org/10.1080/02664760902914458pt_BR
dc.identifier.issn0266-4763pt_BR
dc.identifier.issn1360-0532pt_BR
dc.identifier.issue5pt_BR
dc.identifier.urihttps://repositorio.insper.edu.br/handle/11224/4216
dc.identifier.volume37pt_BR
dc.language.isoInglêspt_BR
dc.publisherTaylor & Francispt_BR
dc.relation.ispartofJournal of Applied Statisticspt_BR
dc.rights.licenseO INSPER E ESTE REPOSITÓRIO NÃO DETÊM OS DIREITOS DE USO E REPRODUÇÃO DOS CONTEÚDOS AQUI REGISTRADOS. É RESPONSABILIDADE DOS USUÁRIOS INDIVIDUAIS VERIFICAR OS USOS PERMITIDOS NA FONTE ORIGINAL, RESPEITANDO-SE OS DIREITOS DE AUTOR OU EDITOR;pt_BR
dc.subject.keywordsACD modelpt_BR
dc.subject.keywordsbootstrappt_BR
dc.subject.keywordsdurationspt_BR
dc.subject.keywordsnon-stationaritypt_BR
dc.subject.keywordstime-varying parameterspt_BR
dc.subject.keywordswaveletpt_BR
dc.subject.otherEstatísticapt_BR
dc.titleTime-varying autoregressive conditional duration modelpt_BR
dc.typejournal article
dspace.entity.typePublication
local.identifier.sourceUrihttps://www.tandfonline.com/doi/abs/10.1080/02664760902914458
local.subject.cnpqCiências Exatas e da Terrapt_BR
local.typeArtigo Científicopt_BR
relation.isAuthorOfPublicationccfd47d5-bd80-4464-98ce-629abb672e3d
relation.isAuthorOfPublication.latestForDiscoveryccfd47d5-bd80-4464-98ce-629abb672e3d
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