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Validating multiple-period density-forecasting models

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  • Kevin Dowd

    (Nottingham University Business School, Nottingham, UK)

Abstract

This paper examines the problem of how to validate multiple-period density forecasting models. Such models are more difficult to validate than their single-period equivalents, because consecutive observations are subject to common shocks that undermine i.i.d. The paper examines various solutions to this problem, and proposes a new solution based on the application of standard tests to a resample that is constructed to be i.i.d. It suggests that this solution is superior to alternatives, and presents results indicating that tests based on the i.i.d. resample approach have good power. Copyright © 2007 John Wiley & Sons, Ltd.

Suggested Citation

  • Kevin Dowd, 2007. "Validating multiple-period density-forecasting models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(4), pages 251-270.
    • Handle: RePEc:jof:jforec:v:26:y:2007:i:4:p:251-270
    DOI: 10.1002/for.1025
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    References listed on IDEAS

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    6. Anthony Tay & Kenneth F. Wallis, 2000. "Density Forecasting: A Survey," Econometric Society World Congress 2000 Contributed Papers 0370, Econometric Society.
    7. M. C. Jones & M. J. Faddy, 2003. "A skew extension of the t‐distribution, with applications," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 159-174, February.
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    Cited by:

    1. Carl Lönnbark, 2016. "Approximation methods for multiple period Value at Risk and Expected Shortfall prediction," Quantitative Finance, Taylor & Francis Journals, vol. 16(6), pages 947-968, June.

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