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Forecasts in a slightly misspecified finite order var
Müller, Ulrich K.; Stock, James H. - 2011
finite order autoregression. We model the innovations as having a log-spectral density that is a continuous mean …
Persistent link: https://www.econbiz.de/10008825323
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Modelling economic high-frequency time series
Lundbergh, Stefan; Teräsvirta, Timo - 1999
In this paper we introduce the STAR-STGARCH model that can characterizenonlinear behaviour both in the conditional mean and the conditionalvariance. A modelling cycle for this family of models, consisting ofspecification, estimation, and evaluation stages is constructed.Misspecification tests...
Persistent link: https://www.econbiz.de/10011300552
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Modelling autoregressive processes with a shifting mean
González, Andrés; Teräsvirta, Timo - In: Studies in nonlinear dynamics and econometrics : SNDE ; … 12 (2008) 1, pp. 1-26
Persistent link: https://www.econbiz.de/10009513641
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Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series : a reexamination
Teräsvirta, Timo (contributor); Dijk, Dick van (contributor) - 2004 - [Elektronische Ressource]
Persistent link: https://www.econbiz.de/10002220582
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Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series : a re-examination
Teräsvirta, Timo (contributor); Dijk, Dick van (contributor) - 2004 - [Elektronische Ressource], Rev. November 9, 2004
In this paper we examine the forecast accuracy of linear autoregressive, smooth transition autoregressive (STAR), and neural network (NN) time series models for 47 monthly macroeconomic variables of the G7 economies. Unlike previous studies that typically consider multiple but fixed model...
Persistent link: https://www.econbiz.de/10002127012
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A time series model for an exchange rate in a target zone with applications
Lundbergh, Stefan; Teräsvirta, Timo - In: Journal of econometrics 131 (2006) 1/2, pp. 579-609
Persistent link: https://www.econbiz.de/10003298619
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Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series : a re-examination
Teräsvirta, Timo; Dijk, Dick van; Medeiros, Marcelo C. - In: International journal of forecasting 21 (2005) 4, pp. 755-774
Persistent link: https://www.econbiz.de/10003150707
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Comments on "Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series : a re-examination
Novales, Alfonso - In: International journal of forecasting 21 (2005) 4, pp. 775-780
Persistent link: https://www.econbiz.de/10003150708
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Reply: [Comments on "Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series : a re-examination]
Teräsvirta, Timo; Dijk, Dick van; Medeiros, Marcelo C. - In: International journal of forecasting 21 (2005) 4, pp. 781-783
Persistent link: https://www.econbiz.de/10003150710
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Determing the number of regimes in a threshold autoregressive model using smooth transition autoregressions
Strikholm, Birgit (contributor);  … - 2005 - [Elektronische Ressource], Rev. February 11, 2005
transition autoregression as a tool. As the smooth transition model is just an approximation to the threshold autoregressive one …
Persistent link: https://www.econbiz.de/10002535492