Modelling Volatility Cycles: The (MF)2 GARCH Model
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- Christian Conrad & Robert F. Engle, 2025. "Modelling Volatility Cycles: The MF2‐GARCH Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(4), pages 438-454, June.
References listed on IDEAS
- Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011.
"Intra-daily Volume Modeling and Prediction for Algorithmic Trading,"
Journal of Financial Econometrics, Oxford University Press, vol. 9(3), pages 489-518, Summer.
- Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2009. "Intra-daily Volume Modeling and Prediction for Algorithmic Trading," Econometrics Working Papers Archive wp2009_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
- Tim Bollerslev & Benjamin Hood & John Huss & Lasse Heje Pedersen, 2018.
"Risk Everywhere: Modeling and Managing Volatility,"
The Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2729-2773.
- Pedersen, Lasse Heje & Bollerslev, Tim & Hood, Benjamin & Huss, John, 2018. "Risk Everywhere: Modeling and Managing Volatility," CEPR Discussion Papers 12687, C.E.P.R. Discussion Papers.
- Amendola, A. & Candila, V. & Cipollini, F. & Gallo, G.M., 2024.
"Doubly multiplicative error models with long- and short-run components,"
Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
- Alessandra Amendola & Vincenzo Candila & Fabrizio Cipollini & Giampiero M. Gallo, 2020. "Doubly Multiplicative Error Models with Long- and Short-run Components," Papers 2006.03458, arXiv.org.
- Fulvio Corsi & Roberto Renò, 2012. "Discrete-Time Volatility Forecasting With Persistent Leverage Effect and the Link With Continuous-Time Volatility Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 368-380, January.
- Bollerslev, Tim & Ghysels, Eric, 1996.
"Periodic Autoregressive Conditional Heteroscedasticity,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 14(2), pages 139-151, April.
- Bollerslev, T. & Ghysels, E., 1994. "Periodic Autoregressive Conditional Heteroskedasticity," Cahiers de recherche 9408, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- Bollerslev, T. & Ghysels, E., 1994. "Periodic Autoregressive Conditional Heteroskedasticity," Cahiers de recherche 9408, Universite de Montreal, Departement de sciences economiques.
- Peter R. Hansen & Asger Lunde & James M. Nason, 2011.
"The Model Confidence Set,"
Econometrica, Econometric Society, vol. 79(2), pages 453-497, March.
- Peter R. Hansen & Asger Lunde & James M. Nason, 2010. "The Model Confidence Set," CREATES Research Papers 2010-76, Department of Economics and Business Economics, Aarhus University.
- Franc Klaassen, 2002. "Improving GARCH volatility forecasts with regime-switching GARCH," Empirical Economics, Springer, vol. 27(2), pages 363-394.
- 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," CREATES Research Papers 2011-01, Department of Economics and Business Economics, Aarhus University.
- Cristina Amado & Timo Teräsvirta, 2011. "Modelling Volatility by Variance Decomposition," NIPE Working Papers 01/2011, NIPE - Universidade do Minho.
- 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.
- 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.
- Andrew J. Patton, 2020. "Comparing Possibly Misspecified Forecasts," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(4), pages 796-809, October.
- Robert F. Engle & Eric Ghysels & Bumjean Sohn, 2013. "Stock Market Volatility and Macroeconomic Fundamentals," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 776-797, July.
- Jon Danielsson & Marcela Valenzuela & Ilknur Zer, 2018.
"Learning from History: Volatility and Financial Crises,"
The Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2774-2805.
- Jón Daníelsson & Marcela Valenzuela & Ilknur Zer, 2016. "Learning from History : Volatility and Financial Crises," Finance and Economics Discussion Series 2016-093, Board of Governors of the Federal Reserve System (U.S.).
- Danielsson, Jon & Valenzuela, Marcela & Zer, Ilknur, 2018. "Learning from history: volatility and financial crises," LSE Research Online Documents on Economics 91136, London School of Economics and Political Science, LSE Library.
- Danielsson, Jon & Valenzuela, Marcela & Zer, Ilknur, 2016. "Learning from history: volatility and financial crises," LSE Research Online Documents on Economics 66046, London School of Economics and Political Science, LSE Library.
- Danielsson, Jon & Valenzuela, Marcela & Zer, Ilknur, 2018. "Learning from history: volatility and financial crises," LSE Research Online Documents on Economics 118942, London School of Economics and Political Science, LSE Library.
- Charlotte Christiansen & Maik Schmeling & Andreas Schrimpf, 2012.
"A comprehensive look at financial volatility prediction by economic variables,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 956-977, September.
- Charlotte Christiansen & Maik Schmeling & Andreas Schrimpf, 2010. "A Comprehensive Look at Financial Volatility Prediction by Economic Variables," CREATES Research Papers 2010-58, Department of Economics and Business Economics, Aarhus University.
- Charlotte Christiansen & Maik Schmeling & Andreas Schrimpf, 2012. "A Comprehensive Look at Financial Volatility Prediction by Economic Variables," BIS Working Papers 374, Bank for International Settlements.
- Christian Conrad & Karin Loch, 2015.
"Anticipating Long‐Term Stock Market Volatility,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(7), pages 1090-1114, November.
- Conrad, Christian & Loch, Karin, 2012. "Anticipating Long-Term Stock Market Volatility," Working Papers 0535, University of Heidelberg, Department of Economics.
- Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993.
"On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks,"
Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
- Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993. "On the relation between the expected value and the volatility of the nominal excess return on stocks," Staff Report 157, Federal Reserve Bank of Minneapolis.
- Engle, Robert F & Ng, Victor K, 1993.
"Measuring and Testing the Impact of News on Volatility,"
Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
- Robert F. Engle & Victor K. Ng, 1991. "Measuring and Testing the Impact of News on Volatility," NBER Working Papers 3681, National Bureau of Economic Research, Inc.
- 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.
- Hossein Asgharian & Ai Jun Hou & Farrukh Javed, 2013. "The Importance of the Macroeconomic Variables in Forecasting Stock Return Variance: A GARCH‐MIDAS Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(7), pages 600-612, November.
- Engle, Robert F. & White (the late), Halbert (ed.), 1999. "Cointegration, Causality, and Forecasting: Festschrift in Honour of Clive W. J. Granger," OUP Catalogue, Oxford University Press, number 9780198296836, Decembrie.
- Ding, Zhuanxin & Granger, Clive W. J., 1996. "Modeling volatility persistence of speculative returns: A new approach," Journal of Econometrics, Elsevier, vol. 73(1), pages 185-215, July.
- Peter F. Christoffersen & Francis X. Diebold, 2000.
"How Relevant is Volatility Forecasting for Financial Risk Management?,"
The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 12-22, February.
- Peter F. Christoffersen & Francis X. Diebold, 1997. "How Relevant is Volatility Forecasting for Financial Risk Management?," Center for Financial Institutions Working Papers 97-45, Wharton School Center for Financial Institutions, University of Pennsylvania.
- Peter F. Christoffersen & Francis X. Diebold, 1998. "How Relevant is Volatility Forecasting for Financial Risk Management?," New York University, Leonard N. Stern School Finance Department Working Paper Seires 98-080, New York University, Leonard N. Stern School of Business-.
- Peter F. Christoffersen & Francis X. Diebold, 1998. "How Relevant is Volatility Forecasting for Financial Risk Management?," NBER Working Papers 6844, National Bureau of Economic Research, Inc.
- Asger Lunde & Peter R. Hansen, 2005.
"A forecast comparison of volatility models: does anything beat a GARCH(1,1)?,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
- Asger Lunde & Peter Reinhard Hansen, 2001. "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?," Working Papers 2001-04, Brown University, Department of Economics.
- Christian Conrad & Melanie Schienle, 2020.
"Testing for an Omitted Multiplicative Long-Term Component in GARCH Models,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 229-242, April.
- Conrad, Christian & Schienle, Melanie, 2019. "Testing for an omitted multiplicative long-term component in GARCH models," Working Paper Series in Economics 121, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
- Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2004.
"The MIDAS Touch: Mixed Data Sampling Regression Models,"
University of California at Los Angeles, Anderson Graduate School of Management
qt9mf223rs, Anderson Graduate School of Management, UCLA.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," CIRANO Working Papers 2004s-20, CIRANO.
- 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.
- Patton, Andrew J., 2011.
"Volatility forecast comparison using imperfect volatility proxies,"
Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
- Andrew Patton, 2006. "Volatility Forecast Comparison using Imperfect Volatility Proxies," Research Paper Series 175, Quantitative Finance Research Centre, University of Technology, Sydney.
- Ling, Shiqing & McAleer, Michael, 2002.
"Stationarity and the existence of moments of a family of GARCH processes,"
Journal of Econometrics, Elsevier, vol. 106(1), pages 109-117, January.
- Shiqing Ling & Michael McAleer, 2001. "Stationarity and the Existence of Moments of a Family of GARCH Processes," ISER Discussion Paper 0535, Institute of Social and Economic Research, The University of Osaka.
- Christian Brownlees & Robert F. Engle, 2017.
"SRISK: A Conditional Capital Shortfall Measure of Systemic Risk,"
The Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 48-79.
- Brownlees, Christian & Engle, Robert F., 2017. "SRISK: a conditional capital shortfall measure of systemic risk," ESRB Working Paper Series 37, European Systemic Risk Board.
- David Berger & Ian Dew-Becker & Stefano Giglio, 2020.
"Uncertainty Shocks as Second-Moment News Shocks,"
The Review of Economic Studies, Review of Economic Studies Ltd, vol. 87(1), pages 40-76.
- David Berger & Ian Dew-Becker & Stefano Giglio, 2017. "Uncertainty Shocks as Second-Moment News Shocks," NBER Working Papers 23796, National Bureau of Economic Research, Inc.
- Stefano Giglio & Ian Dew-Becker & David Berger, 2017. "Uncertainty Shocks as Second-Moment News Shocks," 2017 Meeting Papers 403, Society for Economic Dynamics.
- Scott R. Baker & Nicholas Bloom & Steven J. Davis & Kyle J. Kost, 2019. "Policy News and Stock Market Volatility," NBER Working Papers 25720, National Bureau of Economic Research, Inc.
- Drew Creal & Siem Jan Koopman & André Lucas, 2013. "Generalized Autoregressive Score Models With Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 777-795, August.
- Wang, Fangfang & Ghysels, Eric, 2015. "Econometric Analysis Of Volatility Component Models," Econometric Theory, Cambridge University Press, vol. 31(2), pages 362-393, April.
- 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.
- Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," The Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
- Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
- Paye, Bradley S., 2012. "‘Déjà vol’: Predictive regressions for aggregate stock market volatility using macroeconomic variables," Journal of Financial Economics, Elsevier, vol. 106(3), pages 527-546.
- Diebold, Francis X & Mariano, Roberto S, 2002.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
- Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-263, July.
- Francis X. Diebold & Roberto S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Christian Conrad & Onno Kleen, 2020. "Two are better than one: Volatility forecasting using multiplicative component GARCH‐MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 19-45, January.
- Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006.
"Predicting volatility: getting the most out of return data sampled at different frequencies,"
Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," CIRANO Working Papers 2004s-19, CIRANO.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," NBER Working Papers 10914, National Bureau of Economic Research, Inc.
- Halunga, Andreea G. & Orme, Chris D., 2009.
"First-Order Asymptotic Theory For Parametric Misspecification Tests Of Garch Models,"
Econometric Theory, Cambridge University Press, vol. 25(2), pages 364-410, April.
- Andreea Halunga & Chris D. Orme, 2007. "First order asymptotic theory for parametric misspecification tests of GARCH models," Economics Discussion Paper Series 0721, Economics, The University of Manchester.
- Fang, Tong & Lee, Tae-Hwy & Su, Zhi, 2020.
"Predicting the long-term stock market volatility: A GARCH-MIDAS model with variable selection,"
Journal of Empirical Finance, Elsevier, vol. 58(C), pages 36-49.
- Tong Fang & Tae-Hwy Lee & Zhi Su, 2020. "Predicting the Long-term Stock Market Volatility: A GARCH-MIDAS Model with Variable Selection," Working Papers 202009, University of California at Riverside, Department of Economics.
- Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "Financial Mathematics, Volatility and Covariance Modelling," Post-Print halshs-02183052, HAL.
- Peter Reinhard Hansen & Zhuo Huang & Howard Howan Shek, 2012. "Realized GARCH: a joint model for returns and realized measures of volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 877-906, September.
- Engle, Robert F. & Campos-Martins, Susana, 2023. "What are the events that shake our world? Measuring and hedging global COVOL," Journal of Financial Economics, Elsevier, vol. 147(1), pages 221-242.
- Daniel Borup & Johan S. Jakobsen, 2019. "Capturing volatility persistence: a dynamically complete realized EGARCH-MIDAS model," Quantitative Finance, Taylor & Francis Journals, vol. 19(11), pages 1839-1855, November.
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More about this item
Keywords
Volatility forecasting; long- and short-term volatility; mixed frequency data; volatility cycles;All these keywords.
JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2021-03-22 (Econometrics)
- NEP-ETS-2021-03-22 (Econometric Time Series)
- NEP-FOR-2021-03-22 (Forecasting)
- NEP-MAC-2021-03-22 (Macroeconomics)
Statistics
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