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On estimation in conditional heteroskedastic time series models under non-normal distributions

Liu, Shuangzhe; Heyde, C C

Description

Financial time series data are typically observed to have heavy tails and time-varying volatility. Conditional heteroskedastic models to describe this behaviour have received considerable attention. In the present paper, our purpose is to examine some of

dc.contributor.authorLiu, Shuangzhe
dc.contributor.authorHeyde, C C
dc.date.accessioned2015-12-08T22:19:22Z
dc.identifier.issn0932-5026
dc.identifier.urihttp://hdl.handle.net/1885/31539
dc.description.abstractFinancial time series data are typically observed to have heavy tails and time-varying volatility. Conditional heteroskedastic models to describe this behaviour have received considerable attention. In the present paper, our purpose is to examine some of
dc.publisherSpringer
dc.sourceStatistical Papers
dc.subjectKeywords: BHHH method; Heteroskedasticity; Likelihood; Newton-Raphson method
dc.titleOn estimation in conditional heteroskedastic time series models under non-normal distributions
dc.typeJournal article
local.description.notesImported from ARIES
dc.date.issued2006
local.identifier.absfor010406 - Stochastic Analysis and Modelling
local.identifier.ariespublicationu3488905xPUB84
local.type.statusPublished Version
local.contributor.affiliationLiu, Shuangzhe, University of Canberra
local.contributor.affiliationHeyde, C C, College of Physical and Mathematical Sciences, ANU
local.description.embargo2037-12-31
local.identifier.doi10.1007/s00362-006-0026-3
dc.date.updated2015-12-08T08:21:40Z
local.identifier.scopusID2-s2.0-42449098117
CollectionsANU Research Publications

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