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using a Proxy for Downward Price Pressure

By  and Marcel P. Visser and Marcel P. Visser

Abstract

This paper decomposes volatility proxies according to upward and downward price movements in high-frequency financial data, and uses this decomposition for forecasting volatility. The paper introduces a simple Garch-type discrete time model that incorporates such high-frequency based statistics into a forecast equation for daily volatility. Analysis of S&P 500 index tick data over the years 1988–2006 shows that taking into account the downward movements improves forecast accuracy significantly. The R2 statistic for evaluating daily volatility forecasts attains a value of 0.80, both for in-sample and out-of-sample prediction. JEL classification: C22, C53, G10

Topics: Key Words, volatility proxy, downward absolute power variation, log-Garch, volatility asymmetry, leverage effect, SP500, volatility forecasting, high-frequency data
Year: 2008
OAI identifier: oai:CiteSeerX.psu:10.1.1.320.8441
Provided by: CiteSeerX
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