Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model

Annastiina Silvennoinen and Timo Teräsvirta

Econometrics and Statistics, 2024, vol. 32, issue C, 57-72

Abstract: 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)
Date: 2024
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Related works:
Working Paper: Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecosta:v:32:y:2024:i:c:p:57-72

DOI: 10.1016/j.ecosta.2021.07.008

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