Realising the future: forecasting with high-frequency-based volatility (HEAVY) models
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 effec...
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| Veröffentlicht in: | Journal of applied econometrics (Chichester, England) England), 2010-03, Vol.25 (2), p.197-231 |
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| container_issue | 2 |
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| container_title | Journal of applied econometrics (Chichester, England) |
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| creator | Shephard, Neil Sheppard, Kevin |
| description | 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. |
| doi_str_mv | 10.1002/jae.1158 |
| format | Article |
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| ispartof | Journal of applied econometrics (Chichester, England), 2010-03, Vol.25 (2), p.197-231 |
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| source | Wiley Online Library Journals Frontfile Complete; Jstor Complete Legacy |
| subjects | Bootstrap method Econometric models Econometrics Economic models Estimators Forecasting models Forecasting standards Forecasting techniques GARCH models Libraries Modeling Parametric models Rates of return Statistical forecasts Statistical variance Stochastic models Stock returns Studies Time series Time series forecasting Volatility |
| title | Realising the future: forecasting with high-frequency-based volatility (HEAVY) models |
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