Statistical inference for time-varying ARCH processes

dc.creatorDahlhaus, Rainer
dc.creatorRao, Suhasini Subba
dc.date2006-07-31
dc.date.accessioned2026-07-07T08:08:03Z
dc.date.available2026-07-07T08:08:03Z
dc.descriptionIn this paper the class of ARCH$(\infty)$ models is generalized to the nonstationary class of ARCH$(\infty)$ models with time-varying coefficients. For fixed time points, a stationary approximation is given leading to the notation ``locally stationary ARCH$(\infty)$ process.'' The asymptotic properties of weighted quasi-likelihood estimators of time-varying ARCH$(p)$ processes ($p<\infty$) are studied, including asymptotic normality. In particular, the extra bias due to nonstationarity of the process is investigated. Moreover, a Taylor expansion of the nonstationary ARCH process in terms of stationary processes is given and it is proved that the time-varying ARCH process can be written as a time-varying Volterra series.
dc.descriptionPublished at http://dx.doi.org/10.1214/009053606000000227 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/math/0607799
dc.identifierhttp://arxiv.org/abs/math/0607799
dc.identifierAnnals of Statistics 2006, Vol. 34, No. 3, 1075-1114
dc.identifierdoi:10.1214/009053606000000227
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/131131
dc.subjectStatistics Theory
dc.subject62M10 (Primary) 62F10 (Secondary)
dc.titleStatistical inference for time-varying ARCH processes
dc.typetext

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