Contemporaneous-Threshold Smooth Transition GARCH Models
This paper proposes a contemporaneous-threshold smooth transition GARCH (or CSTGARCH) model for dynamic conditional heteroskedasticity. The C-STGARCH model is a generalization to second conditional moments of the contemporaneous smooth transition threshold autoregressive model of Dueker et al. (2007), in which the regime weights depend on the ex ante probability that a contemporaneous latent regime-specific variable exceeds a threshold value. A key feature of the C-STGARCH model is that its transition function depends on all the parameters of the model as well as on the data. These characteristics allow the model to account for the large persistence and regime shifts that are often observed in the conditional second moments of economic and financial time series.
|Date of creation:||Jun 2009|
|Date of revision:|
|Contact details of provider:|| Web page: http://www.utdt.edu/ver_contenido.php?id_contenido=439&id_item_menu=568|
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Pagan, Adrian R. & Schwert, G. William, 1990.
"Alternative models for conditional stock volatility,"
Journal of Econometrics,
Elsevier, vol. 45(1-2), pages 267-290.
- Adrian R. Pagan & G. William Schwert, 1989. "Alternative Models For Conditional Stock Volatility," NBER Working Papers 2955, National Bureau of Economic Research, Inc.
- Pagan, A.R. & Schwert, G.W., 1989. "Alternative Models For Conditional Stock Volatility," Papers 89-02, Rochester, Business - General.
- Lanne, Markku & Saikkonen, Pentti, 2002.
"Nonlinear GARCH models for highly persistent volatility,"
SFB 373 Discussion Papers
2002,20, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- Markku Lanne & Pentti Saikkonen, 2005. "Non-linear GARCH models for highly persistent volatility," Econometrics Journal, Royal Economic Society, vol. 8(2), pages 251-276, 07.
- Lubrano, M., 1999.
"Smooth Transition GARCH Models: a Bayesian perspective,"
99a49, Universite Aix-Marseille III.
- LUBRANO, Michel, 1998. "Smooth transition GARCH models: a Bayesian perspective," CORE Discussion Papers 1998066, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Michel LUBRANO, 2001. "Smooth Transition Garch Models : a Baysian Perspective," Discussion Papers (REL - Recherches Economiques de Louvain) 2001032, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
- Michael Dueker & Martin Sola & Fabio Spagnolo, 2007.
"Contemporaneous Threshold Autoregressive Models: Estimation, Testing and Forecasting,"
5_2007, D.E.S. (Department of Economic Studies), University of Naples "Parthenope", Italy.
- Dueker, Michael J. & Sola, Martin & Spagnolo, Fabio, 2007. "Contemporaneous threshold autoregressive models: Estimation, testing and forecasting," Journal of Econometrics, Elsevier, vol. 141(2), pages 517-547, December.
- Michael Dueker & Martin Sola & Fabio Spagnolo, 2006. "Contemporaneous Threshold Autoregressive Models: Estimation, Testing and Forecasting," Department of Economics Working Papers 2006-04, Universidad Torcuato Di Tella.
- Michael J. Dueker & Martin Sola & Fabio Spagnolo, 2006. "Contemporaneous threshold autoregressive models: estimation, testing and forecasting," Working Papers 2003-024, Federal Reserve Bank of St. Louis.
- Medeiros, Marcelo C. & Veiga, Alvaro, 2009. "Modeling Multiple Regimes In Financial Volatility With A Flexible Coefficient Garch(1,1) Model," Econometric Theory, Cambridge University Press, vol. 25(01), pages 117-161, February.
When requesting a correction, please mention this item's handle: RePEc:udt:wpecon:2009-06. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Martin Cecilia Lafuente)
If references are entirely missing, you can add them using this form.