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Do Jumps Matter? Forecasting Multivariate Realized Volatility allowing for Common Jumps

  • Yin Liao
  • Heather M. Anderson


  • Farshid Vahid


Realized volatility of stock returns is often decomposed into two distinct components that are attributed to continuous price variation and jumps. This paper proposes a tobit multivariate factor model for the jumps coupled with a standard multivariate factor model for the continuous sample path to jointly forecast volatility in three Chinese Mainland stocks. Out of sample forecast analysis shows that separate multivariate factor models for the two volatility processes outperform a single multivariate factor model of realized volatility, and that a single multivariate factor model of realized volatility outperforms univariate models.

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Paper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 11/10.

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Length: 44 pages
Date of creation: May 2010
Date of revision:
Handle: RePEc:msh:ebswps:2010-11
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  6. Fulvio Corsi & Davide Pirino & Roberto Reno, 2009. "Volatility Forecasting: The Jumps Do Matter," Global COE Hi-Stat Discussion Paper Series gd08-036, Institute of Economic Research, Hitotsubashi University.
  7. Bollerslev, Tim & Law, Tzuo Hann & Tauchen, George, 2008. "Risk, jumps, and diversification," Journal of Econometrics, Elsevier, vol. 144(1), pages 234-256, May.
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  17. Lanne, Markku, 2007. "Forecasting realized exchange rate volatility by decomposition," International Journal of Forecasting, Elsevier, vol. 23(2), pages 307-320.
  18. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
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