Evaluating interval forecasts of high-frequency financial data
Abstract
A number of methods of evaluating the validity of interval forecasts of financial data are analysed, and illustrated using intraday FTSE100 index futures returns. Some existing interval forecast evaluation techniques, such as the Markov chain approach of Christoffersen (1998), are shown to be inappropriate in the presence of periodic heteroscedasticity. Instead, we consider a regression-based test, and a modified version of Christoffersen's Markov chain test for independence, and analyse their properties when the financial time series exhibit periodic volatility. These approaches lead to different conclusions when interval forecasts of FTSE100 index futures returns generated by various GARCH(1,1) and periodic GARCH(1,1) models are evaluated. Copyright © 2003 John Wiley & Sons, Ltd.Download Info
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.
Volume (Year): 18 (2003)
Issue (Month): 4 ()
Pages: 445-456
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Wallis, Kenneth F., 2002.
"Chi-squared tests of interval and density forecasts, and the Bank of England's fan charts,"
Royal Economic Society Annual Conference 2002
181, Royal Economic Society.
- Wallis, Kenneth F., 2003. "Chi-squared tests of interval and density forecasts, and the Bank of England's fan charts," International Journal of Forecasting, Elsevier, vol. 19(2), pages 165-175.
- Kenneth F. Wallis, 2001. "Chi-squared tests of interval and density forecasts and the Bank of England's fan charts," Working Paper Series 083, European Central Bank.
- Taylor, Nicholas, 2007. "A note on the importance of overnight information in risk management models," Journal of Banking & Finance, Elsevier, vol. 31(1), pages 161-180, January.
- Tsyplakov, Alexander, 2011. "Evaluating density forecasts: a comment," MPRA Paper 31184, University Library of Munich, Germany.
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