Time-Varying Autoregressive Conditional Duration Model

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dc.contributor.authorADRIANA BRUSCATO BORTOLUZZO
dc.contributor.authorMorettin, Pedro A.
dc.contributor.authorToloi, Clelia M. C.
dc.coverage.cidadeSão Paulopt_BR
dc.coverage.paisBrasilpt_BR
dc.creatorMorettin, Pedro A.
dc.creatorToloi, Clelia M. C.
dc.date.accessioned2023-07-13T20:35:28Z
dc.date.available2023-07-13T20:35:28Z
dc.date.issued2009
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 time-varying ACD model simultaneously modelled the dependence between durations, intra-day seasonality and volatility.pt_BR
dc.format.extent21 p.pt_BR
dc.format.mediumDigitalpt_BR
dc.identifier.issueBEWP 059/2009
dc.identifier.urihttps://repositorio.insper.edu.br/handle/11224/5758
dc.language.isoInglêspt_BR
dc.publisherInsperpt_BR
dc.publisherIBMEC São Paulopt_BR
dc.relation.ispartofseriesInsper Working Paperpt_BR
dc.rights.licenseO INSPER E ESTE REPOSITÓRIO NÃO DETÊM OS DIREITOS DE USO E REPRODUÇÃO DOS CONTEÚDOS AQUI REGISTRADOS. É RESPONSABILIDADE DO USUÁRIO VERIFICAR OS USOS PERMITIDOS NA FONTE ORIGINAL, RESPEITANDO-SE OS DIREITOS DE AUTOR OU EDITORpt_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.titleTime-Varying Autoregressive Conditional Duration Modelpt_BR
dc.typeworking paper
dspace.entity.typePublication
local.subject.cnpqCiências Exatas e da Terrapt_BR
local.typeWorking Paperpt_BR
relation.isAuthorOfPublicationccfd47d5-bd80-4464-98ce-629abb672e3d
relation.isAuthorOfPublication.latestForDiscoveryccfd47d5-bd80-4464-98ce-629abb672e3d

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Coleção Insper Business and Economics Working Papers