Level changes in volatility models
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DOI: 10.1007/s10436-010-0163-5
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- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007.
"Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility,"
The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2005. "Roughing it Up: Including Jump Components in the Measurement, Modeling and Forecasting of Return Volatility," NBER Working Papers 11775, National Bureau of Economic Research, Inc.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling and Forecasting of Return Volatility," CREATES Research Papers 2007-18, Department of Economics and Business Economics, Aarhus University.
- Christian Francq & Michel Roussignol & Jean‐Michel Zakoian, 2001.
"Conditional Heteroskedasticity Driven by Hidden Markov Chains,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 22(2), pages 197-220, March.
- Christian Francq & Michel Roussignol & Jean-Michel Zakoïan, 1998. "Conditional Heteroskedasticity Driven by Hidden Markov Chains," Working Papers 98-45, Center for Research in Economics and Statistics.
- Francq, Christian & Roussignol, Michel & Zakoian, Jean-Michel, 1998. "Conditional heteroskedasticity driven by hidden Markov chains," SFB 373 Discussion Papers 1998,86, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- Smith, Aaron, 2005.
"Level Shifts and the Illusion of Long Memory in Economic Time Series,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 321-335, July.
- Smith, Aaron D., 2004. "Level Shifts and the Illusion of Long Memory in Economic Time Series," Working Papers 11974, University of California, Davis, Department of Agricultural and Resource Economics.
- Granger, Clive W. J. & Terasvirta, Timo, 1999.
"A simple nonlinear time series model with misleading linear properties,"
Economics Letters, Elsevier, vol. 62(2), pages 161-165, February.
- Granger, Clive W.J. & Teräsvirta, Timo, 1998. "A simple nonlinear time series model with misleading linear properties," SSE/EFI Working Paper Series in Economics and Finance 237, Stockholm School of Economics.
- Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008.
"Designing Realized Kernels to Measure the ex post Variation of Equity Prices in the Presence of Noise,"
Econometrica, Econometric Society, vol. 76(6), pages 1481-1536, November.
- Ole E Barndorff-Nielsen & Peter Hansen & Asger Lunde & Neil Shephard, 2006. "Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise," OFRC Working Papers Series 2006fe05, Oxford Financial Research Centre.
- Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2006. "Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise," Economics Papers 2006-W03, Economics Group, Nuffield College, University of Oxford.
- 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(1), pages 117-161, February.
- Bai, Jushan, 1997.
"Estimating Multiple Breaks One at a Time,"
Econometric Theory, Cambridge University Press, vol. 13(3), pages 315-352, June.
- Jushan Bai, 1995. "Estimating Multiple Breaks One at a Time," Working papers 95-18, Massachusetts Institute of Technology (MIT), Department of Economics.
- Lobato, Ignacio N & Savin, N E, 1998.
"Real and Spurious Long-Memory Properties of Stock-Market Data,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 261-268, July.
- Lobato, I.N. & Savin, N.E., 1996. "Real and Spurious Long Memory Properties of Stock Market Data," Working Papers 96-07, University of Iowa, Department of Economics.
- I.N. Lobato & N.E. Savin, 1996. "Real and Spurious Long Memory Properties of Stock Market Data," Econometrics 9605004, University Library of Munich, Germany, revised 26 Sep 1996.
- Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
- Sylvia Kaufmann & Sylvia Frühwirth‐Schnatter, 2002.
"Bayesian analysis of switching ARCH models,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 23(4), pages 425-458, July.
- Sylvia Fruhwirth-Schnattaer & Sylvia Kaufmann, 2000. "Bayesian Analysis of Switching ARCH Models," Econometric Society World Congress 2000 Contributed Papers 1381, Econometric Society.
- Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
- 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.
- Jushan Bai & Pierre Perron, 1998.
"Estimating and Testing Linear Models with Multiple Structural Changes,"
Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
- Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche 9552, Universite de Montreal, Departement de sciences economiques.
- Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche 9552, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- Davidson, James & Sibbertsen, Philipp, 2005.
"Generating schemes for long memory processes: regimes, aggregation and linearity,"
Journal of Econometrics, Elsevier, vol. 128(2), pages 253-282, October.
- Davidson, James & Sibbertsen, Philipp, 2002. "Generating schemes for long memory processes: Regimes, aggregation and linearity," Technical Reports 2002,46, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
- Han, Heejoon & Park, Joon Y., 2008.
"Time series properties of ARCH processes with persistent covariates,"
Journal of Econometrics, Elsevier, vol. 146(2), pages 275-292, October.
- Han, Heejoon & Park, Joon Y., 2006. "Time series properties of ARCH processes with persistent covariates," MPRA Paper 5199, University Library of Munich, Germany.
- 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.
- David E. Rapach & Jack K. Strauss, 2008. "Structural breaks and GARCH models of exchange rate volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 65-90.
- Perron, Pierre, 1990.
"Testing for a Unit Root in a Time Series with a Changing Mean,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 153-162, April.
- Perron, P., 1989. "Testing For A Unit Root In A Time Series With A Changing Mean," Papers 347, Princeton, Department of Economics - Econometric Research Program.
- 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.
- Perron, Pierre, 1989.
"The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis,"
Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
- Perron, P, 1988. "The Great Crash, The Oil Price Shock And The Unit Root Hypothesis," Papers 338, Princeton, Department of Economics - Econometric Research Program.
- Lumsdaine, Robin L, 1996. "Consistency and Asymptotic Normality of the Quasi-maximum Likelihood Estimator in IGARCH(1,1) and Covariance Stationary GARCH(1,1) Models," Econometrica, Econometric Society, vol. 64(3), pages 575-596, May.
- Lobato, Ignacio N & Savin, N E, 1998. "Real and Spurious Long-Memory Properties of Stock-Market Data: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 280-283, July.
- Hillebrand, Eric, 2005. "Neglecting parameter changes in GARCH models," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 121-138.
- Hamilton, James D. & Susmel, Raul, 1994.
"Autoregressive conditional heteroskedasticity and changes in regime,"
Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
- Tom Doan, "undated". "RATS programs to estimate Hamilton-Susmel Markov Switching ARCH model," Statistical Software Components RTZ00083, Boston College Department of Economics.
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Cited by:
- Eric Hillebrand & Marcelo C. Medeiros, 2016.
"Nonlinearity, Breaks, and Long-Range Dependence in Time-Series Models,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 23-41, January.
- Eric Hillebrand & Marcelo C. Medeiros, 2012. "Nonlinearity, Breaks, and Long-Range Dependence in Time-Series Models," CREATES Research Papers 2012-30, Department of Economics and Business Economics, Aarhus University.
- Han, Heejoon & Park, Joon Y., 2014. "GARCH with omitted persistent covariate," Economics Letters, Elsevier, vol. 124(2), pages 248-254.
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More about this item
Keywords
Level shifts; Stochastic volatility; Persistence; Realized volatility; HAR-RV; ARMA; VAR; GARCH; C22; C51;All these keywords.
JEL classification:
- 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
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