Modelling Short-Term Volatility with GARCH and Harch Models

17 Pages Posted: 25 Jun 1997

See all articles by Michel M. Dacorogna

Michel M. Dacorogna

PRS Solutions

Ulrich A. Müller

Olsen & Associates

Olivier V. Pictet

Pictet Asset Management

Richard B. Olsen

Lykke Corp; Olsen & Associates

Multiple version iconThere are 2 versions of this paper

Abstract

In this paper we present both a new formulation of the HARCH process and a study of the forecasting accuracy of ARCH-type models for predicting short-term volatility. Using high frequency data, the market volatility is expressed in terms of partial volatilities which are formally exponential moving averages of squared returns measured at different frequencies. This new formulation is shown to produce more accurate fits to the data and, at the same time, to be easier to compute than the earlier version of the HARCH process. This is obtained without losing the nice property of the HARCH process to identify different market components. In a second part, some performance measures of forecasting accuracy are discussed and the ARCH-type models are shown to be good predictors of the short-term hourly historical volatility with the new formulation of the HARCH process being the best predictor.

JEL Classification: G12, G14, C22, C32

Suggested Citation

Dacorogna, Michel M. and Müller, Ulrich A. and Pictet, Olivier V. and Olsen, Richard B., Modelling Short-Term Volatility with GARCH and Harch Models. Available at SSRN: https://ssrn.com/abstract=36960 or http://dx.doi.org/10.2139/ssrn.36960

Michel M. Dacorogna (Contact Author)

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Ulrich A. Müller

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Olivier V. Pictet

Pictet Asset Management ( email )

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Richard B. Olsen

Lykke Corp ( email )

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