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

Neil Shephard
	Oxford-Man Institute, University of Oxford, Eagle House, Walton Well Road, Oxford OX2 6EE, UK
	and Department of Economics, University of Oxford
Kevin Sheppard	
	Department of Economics, University of Oxford, Manor Road Building, Manor Road, Oxford, OX1 3UQ, UK
	and Oxford-Man Institute, University of Oxford
	
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 analyse 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.