Augmented GARCH (p,q) process and its diffusion limit.
A family of parametric GARCH models, defined in terms of an auxiliary process and referred to as the augmented GARCH process is characterized and this process is shown to contain many existing parametric GARCH models. The augmented GARCH process can serve as a general alternative for Language Multi...
| Published in: | Journal of Econometrics Vol. 79; pp. 97 - 128 |
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| Format: | Article |
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Elsevier Science
July 1997
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=513016996&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 513016996 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 03044076 ECM jtl: Journal of Econometrics issn: 03044076 maglogo: N pubinfo: dt: July 1997 vid: 79 pid: 1004 pub: Elsevier Science artinfo: ui: 513016996 10.1016/S0304-4076(97)00009-2 ppf: 97 ppct: 31 formats: tig: atl: Augmented GARCH (p,q) process and its diffusion limit. aug: au: Duan, Jin-Chuan su: Time series analysis Mathematical transformations Stochastic processes Diffusion processes sug: subj: Time series analysis Mathematical transformations Stochastic processes Diffusion processes ab: A family of parametric GARCH models, defined in terms of an auxiliary process and referred to as the augmented GARCH process is characterized and this process is shown to contain many existing parametric GARCH models. The augmented GARCH process can serve as a general alternative for Language Multiplier test of many existing GARCH specifications. The diffusion limit of the augmented GARCH process is shown to contain many bivariate diffusion processes that are commonly used for modeling stochastic volatility in the finance literature. This convergence result generalizes that of Nelson (1990a) to cover a substantially larger class of GARCH(1,1) models and also extends to the GARCH(p,q) specification. The augmented GARCH process can be used as a direct approximation to the stochastic volatility models, or as the score generator in the efficient method of moments (Gallant and Tauchen, 1996) estimation of these models. Reprinted by permission of the publisher. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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