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Realising the future: forecasting with high-frequency-based volatility (HEAVY) models

Listed author(s):
  • Neil Shephard
  • Kevin Sheppard

This paper studies in some detail a class of high-frequency-based volatility (HEAVY) models. These models are direct models of daily asset return volatility based on realised measures constructed from high-frequency data. Our analysis identifies that the models have momentum and mean reversion effects, and that they adjust quickly to structural breaks in the level of the volatility process. We study how to estimate the models and how they perform through the credit crunch, comparing their fit to more traditional GARCH models. We analyse a model-based bootstrap which allows us to estimate the entire predictive distribution of returns. We also provide an analysis of missing data in the context of these models. Copyright © 2010 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/jae.1158
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File URL: http://qed.econ.queensu.ca:80/jae/2010-v25.2/
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 25 (2010)
Issue (Month): 2 ()
Pages: 197-231

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Handle: RePEc:jae:japmet:v:25:y:2010:i:2:p:197-231
DOI: 10.1002/jae.1158
Contact details of provider: Web page: http://www.interscience.wiley.com/jpages/0883-7252/

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