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Citations for "Are there Structural Breaks in Realized Volatility?"

by Chun Liu & John M Maheu

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  1. BAUWENS, Luc & ROMBOUTS, Jeroen, 2009. "On marginal likelihood computation in change-point models," CORE Discussion Papers, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) 2009061, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  2. Stefano Grassi & Paolo Santucci de Magistris, 2013. "It’s all about volatility (of volatility): evidence from a two-factor stochastic volatility model," CREATES Research Papers 2013-03, School of Economics and Management, University of Aarhus.
  3. Casson, Catherine & Fry, J. M. & Casson, Mark, 2011. "Evolution or revolution? a study of price and wage volatility in England, 1200-1900," MPRA Paper 31518, University Library of Munich, Germany.
  4. Chun Liu & John M Maheu, 2008. "Forecasting Realized Volatility: A Bayesian Model Averaging Approach," Working Papers, University of Toronto, Department of Economics tecipa-313, University of Toronto, Department of Economics.
  5. Chevallier, Julien, 2011. "Detecting instability in the volatility of carbon prices," Energy Economics, Elsevier, Elsevier, vol. 33(1), pages 99-110, January.
  6. Julien Chevallier & Benoît Sévi, 2011. "On the realized volatility of the ECX CO 2 emissions 2008 futures contract: distribution, dynamics and forecasting," Annals of Finance, Springer, Springer, vol. 7(1), pages 1-29, February.
  7. Nonejad, Nima, 2014. "Particle Gibbs with Ancestor Sampling Methods for Unobserved Component Time Series Models with Heavy Tails, Serial Dependence and Structural Breaks," MPRA Paper 55664, University Library of Munich, Germany.
  8. Stefano Grassi & Nima Nonejad & Paolo Santucci de Magistris, 2014. "Forecasting with the Standardized Self-Perturbed Kalman Filter," CREATES Research Papers 2014-12, School of Economics and Management, University of Aarhus.
  9. Julien Chevallier & Yannick Le Pen & Benoît Sévi, 2009. "Options introduction and volatility in the EU ETS," EconomiX Working Papers 2009-33, University of Paris West - Nanterre la Défense, EconomiX.
  10. Zhongfang He & John M Maheu, 2008. "Real Time Detection of Structural Breaks in GARCH Models," Working Papers, University of Toronto, Department of Economics tecipa-336, University of Toronto, Department of Economics.
  11. Nima Nonejad, 2013. "Long Memory and Structural Breaks in Realized Volatility: An Irreversible Markov Switching Approach," CREATES Research Papers 2013-26, School of Economics and Management, University of Aarhus.
  12. John M. Maheu & Yong Song, 2012. "A New Structural Break Model with Application to Canadian Inflation Forecasting," Working Paper Series, The Rimini Centre for Economic Analysis 27_12, The Rimini Centre for Economic Analysis.
  13. Maheu, John M. & McCurdy, Thomas H., 2011. "Do high-frequency measures of volatility improve forecasts of return distributions?," Journal of Econometrics, Elsevier, Elsevier, vol. 160(1), pages 69-76, January.
  14. Liu, Chun, 2010. "Marginal likelihood calculation for gelfand-dey and Chib Method," MPRA Paper 34928, University Library of Munich, Germany.
  15. Julien Chevallier & Benoît Sévi, 2009. "On the realized volatility of the ECX CO2 emissions 2008 futures contract: distribution, dynamics and forecasting," Working Papers halshs-00387286, HAL.
  16. Maheu, John M. & Song, Yong, 2014. "A new structural break model, with an application to Canadian inflation forecasting," International Journal of Forecasting, Elsevier, Elsevier, vol. 30(1), pages 144-160.
  17. He, Zhongfang, 2009. "Forecasting output growth by the yield curve: the role of structural breaks," MPRA Paper 28208, University Library of Munich, Germany.
  18. Chen, Wei-Peng & Choudhry, Taufiq & Wu, Chih-Chiang, 2013. "The extreme value in crude oil and US dollar markets," Journal of International Money and Finance, Elsevier, Elsevier, vol. 36(C), pages 191-210.
  19. Lin, Edward M.H. & Chen, Cathy W.S. & Gerlach, Richard, 2012. "Forecasting volatility with asymmetric smooth transition dynamic range models," International Journal of Forecasting, Elsevier, Elsevier, vol. 28(2), pages 384-399.
  20. Liu, Chun & Liu, Qing, 2012. "Marginal likelihood calculation for the Gelfand–Dey and Chib methods," Economics Letters, Elsevier, Elsevier, vol. 115(2), pages 200-203.
  21. Nima Nonejad, 2013. "A Mixture Innovation Heterogeneous Autoregressive Model for Structural Breaks and Long Memory," CREATES Research Papers 2013-24, School of Economics and Management, University of Aarhus.