Please use this identifier to cite or link to this item: https://doi.org/10.1111/1467-9892.00296
DC FieldValue
dc.titleEstimating the ARCH parameters by solving linear equations
dc.contributor.authorBose, A.
dc.contributor.authorMurherjee, K.
dc.date.accessioned2014-10-28T05:11:51Z
dc.date.available2014-10-28T05:11:51Z
dc.date.issued2003-03
dc.identifier.citationBose, A., Murherjee, K. (2003-03). Estimating the ARCH parameters by solving linear equations. Journal of Time Series Analysis 24 (2) : 127-136. ScholarBank@NUS Repository. https://doi.org/10.1111/1467-9892.00296
dc.identifier.issn01439782
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/105124
dc.description.abstractThis paper discusses the asymptotics of two-stage least squares estimator of the parameters of ARCH models. The estimator is easy to obtain since it involves solving two sets of linear equations. At the same time, the estimator has the same asymptotic efficiency as that of the widely used quasi-maximum likelihood estimator. Simulation results show that, even for small sample size, the performance of our estimator compared to the quasi-maximum likelihood estimator is better.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1111/1467-9892.00296
dc.sourceScopus
dc.subjectArch models
dc.subjectMartingale central limit theorem
dc.subjectQuasi maximum likelihood estimation
dc.subjectStationary and ergodic process
dc.typeArticle
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.doi10.1111/1467-9892.00296
dc.description.sourcetitleJournal of Time Series Analysis
dc.description.volume24
dc.description.issue2
dc.description.page127-136
dc.description.codenJTSAD
dc.identifier.isiut000182292000001
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