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dc.contributor.authorFeng, Cong
dc.date.accessioned2014-03-04T20:35:37Z
dc.date.available2014-03-04T20:35:37Z
dc.date.issued2012-08
dc.identifier.otherfeng_cong_201208_phd
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/feng_cong_201208_phd
dc.identifier.urihttp://hdl.handle.net/10724/28258
dc.description.abstractWe consider a class of semiparametric GARCH models with additive autoregressive components linked together by a dynamic coefficient. We propose estimators for the additive components and the dynamic coefficient based on spline smoothing. The estimation procedure involves only a small number of least squares operations, thus it is computationally efficient. Under regularity conditions, the proposed estimator of the parameter is root-n consistent and asymptotically normal. A simultaneous confidence band for the nonparametric component is proposed by an efficient one-step spline back-fitting. The performance of our method is evaluated by various simulated processes and a financial return series. For the empirical financial return series, we find further statistical evidence of the asymmetric news impact function.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectB-spline, confidence band, knots, news impact curve, volatility.
dc.titleNonparametric analysis of time series with complex features
dc.typeDissertation
dc.description.degreePhD
dc.description.departmentStatistics
dc.description.majorStatistics
dc.description.advisorLynne Seymour
dc.description.advisorLily Wang
dc.description.committeeLynne Seymour
dc.description.committeeLily Wang
dc.description.committeeXiangrong Yin
dc.description.committeeT. N. Sriram
dc.description.committeeJaxk Reeves
dc.description.committeeJeongyoun Ahn


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