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The econometrics of randomly spaced financial data: a survey

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dc.affiliation.dptoUC3M. Departamento de EstadĂ­sticaes
dc.contributor.authorMonteiro, André A.
dc.contributor.editorUniversidad Carlos III de Madrid. Departamento de EstadĂ­stica
dc.date.accessioned2009-12-16T11:06:31Z
dc.date.available2009-12-16T11:06:31Z
dc.date.issued2009-12
dc.description.abstractThis paper provides an introduction to the problem of modeling randomly spaced longitudinal data. Although Point Process theory was developed mostly in the sixties and early seventies, only in the nineties did this field of Probability theory attract the attention of researchers working in Financial Econometrics. The large increase, observed since, in the number of different classes of Econometric models for dealing with financial duration data, has been mostly due to the increased availability of both trade-by-trade data from equity markets and daily default and rating migration data from credit markets. This paper provides an overview of the main Econometric models available in the literature for dealing with what is sometimes called tick data. Additionally, a synthesis of the basic theory underlying these models is also presented. Finally, a new theorem dealing with the identifiability of latent intensity factors from point process data, jointly with a heuristic proof, is introduced.
dc.format.mimetypeapplication/pdf
dc.identifier.repecws097924
dc.identifier.urihttps://hdl.handle.net/10016/5995
dc.language.isoeng
dc.relation.ispartofseriesUC3M Working papers. Statistics and Econometrics
dc.relation.ispartofseries09-24
dc.rightsAtribuciĂ³n-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.ecienciaEstadĂ­stica
dc.subject.jelC22
dc.subject.jelC32
dc.subject.jelC34
dc.subject.jelC41
dc.subject.jelG10
dc.subject.otherTick data
dc.subject.otherFinancial duration models
dc.subject.otherPoint processes
dc.subject.otherMigration models
dc.titleThe econometrics of randomly spaced financial data: a survey
dc.typeworking paper*
dspace.entity.typePublication
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