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Long-range dependent curve time series

Li, Degui; Robinson, Peter M; Shang, Han Lin

Description

We introduce methods and theory for functional or curve time series with long- range dependence. The temporal sum of the curve process is shown to be asymp- totically normally distributed, the conditions for this covering a functional version of fractionally integrated autoregressive moving averages. We also construct an estimate of the long-run covariance function, which we use, via functional principal component analysis, in estimating the orthonormal functions spanning the dominant sub-space...[Show more]

dc.contributor.authorLi, Degui
dc.contributor.authorRobinson, Peter M
dc.contributor.authorShang, Han Lin
dc.date.accessioned2019-10-17T00:31:20Z
dc.identifier.issn0162-1459
dc.identifier.urihttp://hdl.handle.net/1885/177006
dc.description.abstractWe introduce methods and theory for functional or curve time series with long- range dependence. The temporal sum of the curve process is shown to be asymp- totically normally distributed, the conditions for this covering a functional version of fractionally integrated autoregressive moving averages. We also construct an estimate of the long-run covariance function, which we use, via functional principal component analysis, in estimating the orthonormal functions spanning the dominant sub-space of the curves. In a semiparametric context, we propose an estimate of the memory parameter, and derive its consistency result. A Monte-Carlo study of finite-sample performance is included, along with two empirical applications. The first of these finds a degree of stability and persistence in intra-day stock returns. The second finds similarity in the extent of long memory in age-specific fertility rates across some developed nations.
dc.format.extent16 pages
dc.format.mimetypeapplication/pdf
dc.language.isoen_AU
dc.publisherAmerican Statistical Association
dc.rights© 2019 American Statistical Association
dc.sourceJournal of the American Statistical Association
dc.subjectCurve process
dc.subjectFunctional FARIMA
dc.subjectFunctional principal component analysis
dc.subjectLimit theorems
dc.subjectLong-range dependence
dc.titleLong-range dependent curve time series
dc.typeJournal article
local.description.notesImported from ARIES
dcterms.dateAccepted2019-04-17
dc.date.issued2019-05-30
local.identifier.absfor010405 - Statistical Theory
local.identifier.absfor010401 - Applied Statistics
local.identifier.ariespublicationu1027566xPUB117
local.publisher.urlhttps://taylorandfrancis.com/
local.type.statusPublished Version
local.contributor.affiliationLi, Degui, University of York
local.contributor.affiliationRobinson, Peter M, London School of Economics
local.contributor.affiliationShang, Hanlin, College of Business and Economics, The Australian National University
local.description.embargo2037-12-31
local.identifier.doi10.1080/01621459.2019.1604362
dc.date.updated2019-05-05T09:04:52Z
CollectionsANU Research Publications

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