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Evaluating interval forecasts of high-frequency financial data

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  • Michael P. Clements

    (Department of Economics, University of Warwick, Coventry CV4 7AL, UK)

  • Nick Taylor

    (Department of Accounting and Finance, Cardiff University, UK)

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.

Suggested Citation

  • Michael P. Clements & Nick Taylor, 2003. "Evaluating interval forecasts of high-frequency financial data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 445-456.
    • Handle: RePEc:jae:japmet:v:18:y:2003:i:4:p:445-456
    DOI: 10.1002/jae.703
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    References listed on IDEAS

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