Contemporaneous-Threshold Smooth Transition GARCH Models
AbstractThis 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Universidad Torcuato Di Tella in its series Department of Economics Working Papers with number 2009-06.
Length: 21 pages
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
Conditional heteroskedasticity; Smooth transition GARCH; Threshold; Stock returns.;
Other versions of this item:
- Dueker Michael J. & Psaradakis Zacharias & Sola Martin & Spagnolo Fabio, 2011. "Contemporaneous-Threshold Smooth Transition GARCH Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(2), pages 1-25, March.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-09-26 (All new papers)
- NEP-ECM-2009-09-26 (Econometrics)
- NEP-ETS-2009-09-26 (Econometric Time Series)
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.:
- 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.
- 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, 1990. "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.
- 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).
- Lubrano, M., 1999. "Smooth Transition GARCH Models: a Bayesian perspective," G.R.E.Q.A.M. 99a49, Universite Aix-Marseille III.
- 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).
- 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 Dueker & Martin Sola & Fabio Spagnolo, 2007. "Contemporaneous Threshold Autoregressive Models: Estimation, Testing and Forecasting," Discussion Papers 5_2007, D.E.S. (Department of Economic Studies), University of Naples "Parthenope", Italy.
- 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.
- Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, School of Economics and Management, University of Aarhus.
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.