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An application of the analogy between vector ARCH and vector random coefficient autoregressive models
He, Changli (contributor); Teräsvirta, Timo (contributor) - 2002 - [Elektronische Ressource]
; multivariate volatility model ; random coefficient model ; volatility forecasting …
Persistent link: https://www.econbiz.de/10001714621
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A new non-linear GARCH model
Hagerud, Gustaf E. - 1997
Persistent link: https://www.econbiz.de/10000958392
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Stylized facts of financial time series and three popular models of volatility
Malmsten, Hans (contributor); Teräsvirta, Timo (contributor) - 2004 - [Elektronische Ressource], Rev. September 3, 2004
Properties of three well-known and frequently applied first-order models for modelling and forecasting volatility in … Conditional Heteroskedasticity (GARCH), the Exponential GARCH and the Autoregressive Stochastic Volatility model. The focus is on … heteroskedasticity ; evaluation of volatility models ; exponential GARCH ; GARCH ; modelling return series ; stochastic volatility …
Persistent link: https://www.econbiz.de/10002199620
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Multivariate autoregressive conditional heteroskedasticity with smooth transitions in conditional correlations
Silvennoinen, Annastiina (contributor);  … - 2005 - [Elektronische Ressource], Rev. October 2005
; Dynamic conditional correlation ; Return comovement ; Volatility model evaluation …
Persistent link: https://www.econbiz.de/10002570445
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Fourth moment structure of the GARCH (p, q) process
He, Changli; Teräsvirta, Timo - 1997
Persistent link: https://www.econbiz.de/10000960148
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Ergodicity, mixing, and existence of moments of a class of Markov models with applications to GARCH and ACD models
Meitz, Mika (contributor); Saikkonen, Pentti (contributor) - 2004 - [Elektronische Ressource], First version October 2004, revised December 2005 and April 2007
This paper studies a class of Markov models which consist of two components. Typically, one of the components is observable and the other is unobservable or 'hidden'. Conditions under which (a form of) geometric ergodicity of the unobservable component is inherited by the joint process formed of...
Persistent link: https://www.econbiz.de/10002465203
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Specification and estimation of random effects models with serial correlation of general form
Skoglund, Jimmy (contributor); Karlsson, Sune (contributor) - 2001 - [Elektronische Ressource]
This paper is concerned with maximum likelihood based inference in random effects models with serial correlation. Allowing for individual effects we introduce serial correlation of general form in the time effects as well as the idiosyncratic errors. A straightforward maximum likelihood...
Persistent link: https://www.econbiz.de/10001600058
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A simple efficient GMM estimator of GARCH models
Skoglund, Jimmy (contributor) - 2001 - [Elektronische Ressource]
This paper is concerned with efficient GMM estimation and inference in GARCH models. Sufficient conditions for the estimator to be consistent and asymptotically normal are established for the GARCH(1,1) conditional variance process. In addition efficiency results are obtained in the general...
Persistent link: https://www.econbiz.de/10001600059
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An extended constant conditional correlation GARCH model and its fourth-moment-structure
He, Changli (contributor); Teräsvirta, Timo (contributor) - 2002 - [Elektronische Ressource]
heteroskedasticity ; volatility dynamics …
Persistent link: https://www.econbiz.de/10001693116
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Statistical properties of the asymmetric power ARCH process
He, Changli; Teräsvirta, Timo - 1997
Persistent link: https://www.econbiz.de/10000971492