Modelling Conditional and Unconditional Heteroskedasticity with Smoothly Time-Varying Structure
Author
Abstract
Suggested Citation
Download full text from publisher
Other versions of this item:
- Amado, Cristina & Teräsvirta, Timo, 2008. "Modelling Conditional and Unconditional Heteroskedasticity with Smoothly Time-Varying Structure," SSE/EFI Working Paper Series in Economics and Finance 691, Stockholm School of Economics.
- Christina Amado & Timo Teräsvirta, 2008. "Modelling Conditional and Unconditional Heteroskedasticity with Smoothly Time-Varying Structure," CREATES Research Papers 2008-08, Department of Economics and Business Economics, Aarhus University.
References listed on IDEAS
- Meitz, Mika & Saikkonen, Pentti, 2008.
"Ergodicity, Mixing, And Existence Of Moments Of A Class Of Markov Models With Applications To Garch And Acd Models,"
Econometric Theory, Cambridge University Press, vol. 24(5), pages 1291-1320, October.
- Meitz, Mika & Saikkonen, Pentti, 2004. "Ergodicity, mixing, and existence of moments of a class of Markov models with applications to GARCH and ACD models," SSE/EFI Working Paper Series in Economics and Finance 573, Stockholm School of Economics, revised 20 Apr 2007.
- Mika Meitz & Pentti Saikkonen & University of Helsinki, 2007. "Ergodicity, mixing, and existence of moments of a class of Markov models with applications to GARCH and ACD models," Economics Series Working Papers 327, University of Oxford, Department of Economics.
- Ling, Shiqing & McAleer, Michael, 2003.
"Asymptotic Theory For A Vector Arma-Garch Model,"
Econometric Theory, Cambridge University Press, vol. 19(2), pages 280-310, April.
- Shiqing Ling & Michael McAleer, 2001. "Asymptotic Theory for a Vector ARMA-GARCH Model," ISER Discussion Paper 0549, Institute of Social and Economic Research, Osaka University.
- Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996.
"Fractionally integrated generalized autoregressive conditional heteroskedasticity,"
Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
- Tom Doan, "undated". "RATS programs to replicate Baillie, Bollerslev, Mikkelson FIGARCH results," Statistical Software Components RTZ00009, Boston College Department of Economics.
- Baillie, Richard T. & Morana, Claudio, 2009.
"Modelling long memory and structural breaks in conditional variances: An adaptive FIGARCH approach,"
Journal of Economic Dynamics and Control, Elsevier, vol. 33(8), pages 1577-1592, August.
- Richard T. Baillie & Claudio Morana, 2007. "Modeling Long Memory and Structural Breaks in Conditional Variances: an Adaptive FIGARCH Approach," ICER Working Papers - Applied Mathematics Series 11-2007, ICER - International Centre for Economic Research.
- Richard T. Baillie & Claudio Morana, 2014. "Modeling Long Memory and Structural Breaks in Conditional Variances: An Adaptive FIGARCH Approach," Working Papers 593, Queen Mary University of London, School of Economics and Finance.
- Davidson, Russell & MacKinnon, James G, 1998.
"Graphical Methods for Investigating the Size and Power of Hypothesis Tests,"
The Manchester School of Economic & Social Studies, University of Manchester, vol. 66(1), pages 1-26, January.
- Russell Davidson & James G. MacKinnon, 1994. "Graphical Methods for Investigating the Size and Power of Hypothesis Tests," Working Paper 903, Economics Department, Queen's University.
- Eitrheim, Oyvind & Terasvirta, Timo, 1996.
"Testing the adequacy of smooth transition autoregressive models,"
Journal of Econometrics, Elsevier, vol. 74(1), pages 59-75, September.
- Eitrheim, Øyvind & Teräsvirta, Timo, 1995. "Testing the Adequacy of Smooth Transition Autoregressive Models," SSE/EFI Working Paper Series in Economics and Finance 56, Stockholm School of Economics.
- Bollerslev, Tim, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
- Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Jensen, Søren Tolver & Rahbek, Anders, 2004. "Asymptotic Inference For Nonstationary Garch," Econometric Theory, Cambridge University Press, vol. 20(6), pages 1203-1226, December.
- Berkes, István & Gombay, Edit & Horváth, Lajos & Kokoszka, Piotr, 2004. "SEQUENTIAL CHANGE-POINT DETECTION IN GARCH(p,q) MODELS," Econometric Theory, Cambridge University Press, vol. 20(6), pages 1140-1167, December.
- Wooldridge, Jeffrey M., 1990. "A Unified Approach to Robust, Regression-Based Specification Tests," Econometric Theory, Cambridge University Press, vol. 6(1), pages 17-43, March.
- Lundbergh, Stefan & Terasvirta, Timo, 2002.
"Evaluating GARCH models,"
Journal of Econometrics, Elsevier, vol. 110(2), pages 417-435, October.
- Lundbergh, Stefan & Teräsvirta, Timo, 1998. "Evaluating GARCH models," SSE/EFI Working Paper Series in Economics and Finance 292, Stockholm School of Economics, revised 03 Oct 2001.
- Stefan Lundbergh & Timo Teräsvirta, 1999. "Evaluating GARCH Models," Tinbergen Institute Discussion Papers 99-008/4, Tinbergen Institute.
- Lin, Chien-Fu Jeff & Terasvirta, Timo, 1994. "Testing the constancy of regression parameters against continuous structural change," Journal of Econometrics, Elsevier, vol. 62(2), pages 211-228, June.
- Baillie, Richard T. & Morana, Claudio, 2009.
"Modelling long memory and structural breaks in conditional variances: An adaptive FIGARCH approach,"
Journal of Economic Dynamics and Control, Elsevier, vol. 33(8), pages 1577-1592, August.
- Richard T. Baillie & Claudio Morana, 2007. "Modeling Long Memory and Structural Breaks in Conditional Variances: an Adaptive FIGARCH Approach," ICER Working Papers - Applied Mathematics Series 11-2007, ICER - International Centre for Economic Research.
- Richard T. Baillie & Claudio Morana, 2014. "Modeling Long Memory and Structural Breaks in Conditional Variances: An Adaptive FIGARCH Approach," Working Papers 593, Queen Mary University of London, School of Economics and Finance.
- Richard T. Baillie & Claudio Morana, 2007. "Modeling Long Memory and Structural Breaks in Conditional Variances: An Adaptive FIGARCH Approach," Working Papers 593, Queen Mary University of London, School of Economics and Finance.
- Robert B. Davies, 2002. "Hypothesis testing when a nuisance parameter is present only under the alternative: Linear model case," Biometrika, Biometrika Trust, vol. 89(2), pages 484-489, June.
- Shiqing Ling & W. K. Li, 1997. "Diagnostic checking of nonlinear multivariate time series with multivariate arch errors," Journal of Time Series Analysis, Wiley Blackwell, vol. 18(5), pages 447-464, September.
- Lamoureux, Christopher G & Lastrapes, William D, 1990. "Persistence in Variance, Structural Change, and the GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 225-234, April.
- Robert F. Engle & Jose Gonzalo Rangel, 2005. "The Spline GARCH Model for Unconditional Volatility and its Global Macroeconomic Causes," Working Papers 2005/13, Czech National Bank.
- Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
- Kim, Tae-Hwan & White, Halbert, 2004. "On more robust estimation of skewness and kurtosis," Finance Research Letters, Elsevier, vol. 1(1), pages 56-73, March.
- Timo Terasvirta & Zhenfang Zhao, 2011.
"Stylized facts of return series, robust estimates and three popular models of volatility,"
Applied Financial Economics, Taylor & Francis Journals, vol. 21(1-2), pages 67-94.
- Teräsvirta, Timo & Zhao, Zhenfang, 2007. "Stylized Facts of Return Series, Robust Estimates, and Three Popular Models of Volatility," SSE/EFI Working Paper Series in Economics and Finance 662, Stockholm School of Economics, revised 01 Aug 2007.
- Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Amado, Cristina & Teräsvirta, Timo, 2013.
"Modelling volatility by variance decomposition,"
Journal of Econometrics, Elsevier, vol. 175(2), pages 142-153.
- Cristina Amado & Timo Teräsvirta, 2011. "Modelling Volatility by Variance Decomposition," NIPE Working Papers 01/2011, NIPE - Universidade do Minho.
- Cristina Amado & Timo Teräsvirta, 2011. "Modelling Volatility by Variance Decomposition," CREATES Research Papers 2011-01, Department of Economics and Business Economics, Aarhus University.
- Adnen Ben Nasr & Ahdi Noomen Ajmi & Rangan Gupta, 2014.
"Modelling the volatility of the Dow Jones Islamic Market World Index using a fractionally integrated time-varying GARCH (FITVGARCH) model,"
Applied Financial Economics, Taylor & Francis Journals, vol. 24(14), pages 993-1004, July.
- Adnen Ben Nasr & Ahdi N. Ajmi & Rangan Gupta, 2013. "Modeling the Volatility of the Dow Jones Islamic Market World Index Using a Fractionally Integrated Time Varying GARCH (FITVGARCH) Model," Working Papers 201357, University of Pretoria, Department of Economics.
- McAleer, Michael & Medeiros, Marcelo C., 2008.
"A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries,"
Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
- Michael McAller & Marcelo C. Medeiros, 2007. "A multiple regime smooth transition heterogeneous autoregressive model for long memory and asymmetries," Textos para discussão 544, Department of Economics PUC-Rio (Brazil).
- Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018.
"Models with Multiplicative Decomposition of Conditional Variances and Correlations,"
CREATES Research Papers
2018-14, Department of Economics and Business Economics, Aarhus University.
- Cristina Amado & Annastiina Silvennoinen & Timo Ter¨asvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," NIPE Working Papers 07/2018, NIPE - Universidade do Minho.
- Franses,Philip Hans & Dijk,Dick van, 2000.
"Non-Linear Time Series Models in Empirical Finance,"
Cambridge Books,
Cambridge University Press, number 9780521779654.
- Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415, September.
- Cristina Amado & Timo Teräsvirta, 2017. "Specification and testing of multiplicative time-varying GARCH models with applications," Econometric Reviews, Taylor & Francis Journals, vol. 36(4), pages 421-446, April.
- Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006.
"Multivariate GARCH models: a survey,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
- Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
- BAUWENS, Luc & LAURENT, Sébastien & ROMBOUTS, Jeroen, 2003. "Multivariate GARCH models: a survey," LIDAM Discussion Papers CORE 2003031, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- BAUWENS, Luc & LAURENT, Sébastien & ROMBOUTS, Jeroen VK, 2006. "Multivariate GARCH models: a survey," LIDAM Reprints CORE 1847, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, September.
- Díaz-Hernández, Adán & Constantinou, Nick, 2019. "A multiple regime extension to the Heston–Nandi GARCH(1,1) model," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 162-180.
- Meitz, Mika & Saikkonen, Pentti, 2011.
"Parameter Estimation In Nonlinear Ar–Garch Models,"
Econometric Theory, Cambridge University Press, vol. 27(6), pages 1236-1278, December.
- Mika Meitz & Pentti Saikkonen, 2008. "Parameter estimation in nonlinear AR-GARCH models," CREATES Research Papers 2008-30, Department of Economics and Business Economics, Aarhus University.
- Mika Meitz & Pentti Saikkonen, 2008. "Parameter estimation in nonlinear AR-GARCH models," Economics Series Working Papers 396, University of Oxford, Department of Economics.
- Mika Meitz & Pentti Saikkonen, 2010. "Parameter estimation in nonlinear AR–GARCH models," Koç University-TUSIAD Economic Research Forum Working Papers 1002, Koc University-TUSIAD Economic Research Forum.
- Mika Meitz & Pentti Saikkonen, 2008. "Parameter Estimation in Nonlinear AR-GARCH Models," Economics Working Papers ECO2008/25, European University Institute.
- BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011.
"Volatility models,"
LIDAM Discussion Papers CORE
2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Belkhouja, Mustapha & Boutahary, Mohamed, 2011. "Modeling volatility with time-varying FIGARCH models," Economic Modelling, Elsevier, vol. 28(3), pages 1106-1116, May.
- Duchesne, Pierre, 2006. "Testing for multivariate autoregressive conditional heteroskedasticity using wavelets," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2142-2163, December.
- Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
- Adnen Ben Nasr & Mohamed Boutahar & Abdelwahed Trabelsi, 2010. "Fractionally integrated time varying GARCH model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(3), pages 399-430, August.
- Christensen, Bent Jesper & Nielsen, Morten Ørregaard & Zhu, Jie, 2010.
"Long memory in stock market volatility and the volatility-in-mean effect: The FIEGARCH-M Model,"
Journal of Empirical Finance, Elsevier, vol. 17(3), pages 460-470, June.
- Bent Jesper Christensen & Morten Ørregaard Nielsen & Jie Zhu, 2007. "Long Memory in Stock Market Volatility and the Volatility-in-Mean Effect: The FIEGARCH-M Model," CREATES Research Papers 2007-10, Department of Economics and Business Economics, Aarhus University.
- Bent Jesper Christensen & Jie Zhu & Morten Ø. Nielsen, 2009. "Long Memory In Stock Market Volatility And The Volatility-in-mean Effect: The Fiegarch-m Model," Working Paper 1207, Economics Department, Queen's University.
- Massimiliano Caporin & Michael McAleer, 2011.
"Thresholds, news impact surfaces and dynamic asymmetric multivariate GARCH,"
Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 65(2), pages 125-163, May.
- Massimiliano Caporin & Michael McAleer, 2008. "Thresholds, News Impact Surfaces and Dynamic Asymmetric Multivariate GARCH," "Marco Fanno" Working Papers 0064, Dipartimento di Scienze Economiche "Marco Fanno".
- Caporin, M. & McAleer, M.J., 2010. "Threshold, news impact surfaces and dynamic asymmetric multivariate GARCH," Econometric Institute Research Papers EI 2010-36, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Michael McAleer & Massimiliano Caporin, 2010. "Thresholds, News Impact Surfaces and Dynamic Asymmetric Multivariate GARCH," Working Papers in Economics 10/32, University of Canterbury, Department of Economics and Finance.
- Massimiliano Caporin & Michael McAleer, 2010. "Thresholds, News Impact Surfaces and Dynamic Asymmetric Multivariate GARCH," CIRJE F-Series CIRJE-F-740, CIRJE, Faculty of Economics, University of Tokyo.
- Massimiliano Caporin & Michael McAleer, 2009. "Thresholds, News Impact Surfaces and Dynamic Asymmetric Multivariate GARCH," Documentos de Trabajo del ICAE 2009-11, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
- Massimiliano Caporin & Michael McAleer, 2010. "Thresholds, News Impact Surfaces and Dynamic Asymmetric Multivariate GARCH," CARF F-Series CARF-F-217, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
- Massimiliano Caporin & Michael McAleer, 2010. "Thresholds, News Impact Surfaces and Dynamic Asymmetric Multivariate GARCH," KIER Working Papers 741, Kyoto University, Institute of Economic Research.
- Massimiliano Caporin & Michael McAleer, 2010. "Thresholds, News Impact Surfaces and Dynamic Asymmetric Multivariate GARCH," Working Papers in Economics 10/73, University of Canterbury, Department of Economics and Finance.
- Charfeddine, Lanouar & Ajmi, Ahdi Noomen, 2013. "The Tunisian stock market index volatility: Long memory vs. switching regime," Emerging Markets Review, Elsevier, vol. 16(C), pages 170-182.
- Halkos, George E. & Tsirivis, Apostolos S., 2019. "Effective energy commodity risk management: Econometric modeling of price volatility," Economic Analysis and Policy, Elsevier, vol. 63(C), pages 234-250.
- Babikir, Ali & Gupta, Rangan & Mwabutwa, Chance & Owusu-Sekyere, Emmanuel, 2012.
"Structural breaks and GARCH models of stock return volatility: The case of South Africa,"
Economic Modelling, Elsevier, vol. 29(6), pages 2435-2443.
- Ali Babikir & Rangan Gupta & Chance Mwabutwa & Emmanuel Owusu-Sekyere, 2010. "Structural Breaks and GARCH Models of Stock Return Volatility: The Case of South Africa," Working Papers 201030, University of Pretoria, Department of Economics.
More about this item
Keywords
Conditional heteroskedasticity; Structural change; Lagrange multiplier test; Misspecification test; Nonlinear time series; Time-varying parameter model.;All these keywords.
JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ETS-2008-03-01 (Econometric Time Series)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nip:nipewp:03/2008. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: NIPE (email available below). General contact details of provider: https://edirc.repec.org/data/nipampt.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.