Forecasting the Daily Volatility Defined with High-Frequency Data for the Stock Index WIG

Magłorzata Doman () and Ryszard Doman ()
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Magłorzata Doman: Poznań University of Economics and Business, Poland
Ryszard Doman: Adam Mickiewicz University, Poznań, Poland

Chapter 3 in Acta Universitatis Lodziensis. Folia Oeconomica nr 166/2003 - Modern Methods of Analysis and Forecasting Financial Markets, 2003, vol. 166, pp 37-50 from University of Lodz

Abstract: It is generally acknowledged that squared daily returns on a financial instrument provide a poor approximation of its daily volatility. It was first pointed out by Andersen and Bollerslev that more accurate estimates are obtained with the realized volatility calculated as the sum of squared intraday returns corresponding to high-frequency data. In this paper we show how the volatility forecasts for the stock index WIG provided by the popular GARCH(1,1) improve when instead of daily squared returns they are evaluated against the realized volatility.

Keywords: Forecasting; High-frequency data; Realized volatility; GARCH model (search for similar items in EconPapers)
JEL-codes: C01 E02 F00 G00 (search for similar items in EconPapers)
Date: 2003
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Persistent link: https://EconPapers.repec.org/RePEc:ann:findec:book:y:2003:n:166:ch:03:foe

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