English, Article, Journal or magazine article edition: Parameter estimation in nonlinear AR-GARCH models Mika Meitz; Pentti Saikkonen

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Bookmark: http://trove.nla.gov.au/version/20399
Physical Description
  • preprint
Language
  • English

Edition details

Title
  • Parameter estimation in nonlinear AR-GARCH models
Author
  • Mika Meitz
  • Pentti Saikkonen
Physical Description
  • preprint
Notes
  • RePEc:eui:euiwps:eco2008/​25
  • AR-GARCH, asymptotic normality, consistency, nonlinear time series, quasi maximum likelihood estimation
  • RePEc:aah:create:2008-30
  • This paper develops an asymptotic estimation theory for nonlinear autoregressive models with conditionally heteroskedastic errors. We consider a functional coefficient autoregression of order p (AR(p)) with the conditional variance specified as a general nonlinear first order generalized autoregressive conditional heteroskedasticity (GARCH (1,1)) model. Strong consistency and asymptotic normality of the global Gaussian quasi maximum likelihood (QML) estimator are established under conditions comparable to those recently used in the corresponding linear case. To the best of our knowledge, this paper provides the first results on consistency and asymptotic normality of the QML estimator in nonlinear autoregressive models with GARCH errors.
  • RePEc:oxf:wpaper:396
Language
  • English
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