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

Neil Shephard () and Kevin Sheppard ()

No 438, Economics Series Working Papers from University of Oxford, Department of Economics

Abstract: 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 realized 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 analysis a model based bootstrap which allow us to estimate the entire predictive distribution of returns. We also provide an analysis of missing data in the context of these models.

Keywords: ARCH models; Bootstrap; Missing data; Multiplicative error model; Multistep ahead prediction; Non-nested likelihood ratio test; Realised kernel; Realised volatility (search for similar items in EconPapers)
Date: 2009-07-01
New Economics Papers: this item is included in nep-mst
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Journal Article: Realising the future: forecasting with high-frequency-based volatility (HEAVY) models (2010)
Working Paper: Realising the future: forecasting with high frequency based volatility (HEAVY) models (2009)
Working Paper: Realising the future: forecasting with high frequency based volatility (HEAVY) models (2009)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:oxf:wpaper:438

Access Statistics for this paper

More papers in Economics Series Working Papers from University of Oxford, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Anne Pouliquen ( this e-mail address is bad, please contact ).