Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model
Annastiina Silvennoinen () and
Timo Teräsvirta ()
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Annastiina Silvennoinen: NCER, Queensland University of Technology, Postal: NCER, Queensland University of Technology, Brisbane, Australia
CREATES Research Papers from Department of Economics and Business Economics, Aarhus University
A new multivariate volatility model that belongs to the family of conditional correlation GARCH models is introduced. The GARCH equations of this model contain a multiplicative deterministic component to describe long-run movements in volatility and, in addition, the correlations are deterministically time-varying. Parameters of the model are estimated jointly using maximum likelihood. Consistency and asymptotic normality of maximum likelihood estimators is proved. Numerical aspects of the estimation algorithm are discussed. A bivariate empirical example is provided.
Keywords: deterministically varying correlation; multiplicative time-varying GARCH; multivariate GARCH; nonstationary volatility; smooth transition GARCH (search for similar items in EconPapers)
JEL-codes: C32 C51 C58 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:aah:create:2017-28
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