Article

Forecasting Volatility Using High-Frequency Data

Peter Reinhard Hansen and Asger Lunde

in The Oxford Handbook of Economic Forecasting

Published in print July 2011 | ISBN: 9780195398649
Published online September 2012 | | DOI: http://dx.doi.org/10.1093/oxfordhb/9780195398649.013.0020

Series: Oxford Handbooks

 Forecasting Volatility Using High-Frequency Data

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This article focuses on some aspects of high-frequency data and their use in volatility forecasting. High-frequency data can be used to construct volatility forecasts. The article reviews two leading approaches to this. One approach is the reduced-form forecast, where the forecast is constructed from a time series model for realized measures, or a simple regression-based approach such as the heterogeneous autoregressive model. The other is based on more traditional discrete-time volatility models that include a modeling of returns. Such models can be generalized to utilize information provided by realized measures. The article also discusses how volatility forecasts, produced by complex volatility models, can benefit from high-frequency data in an indirect manner, through the use of realized measures to facilitate and improve the estimation of complex models.

Keywords: high-frequency data; economic forecasting; volatility forecasting

Article.  13296 words. 

Subjects: Economics ; Econometric and Statistical Methods and Methodology: General ; Financial Markets

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