Testing for Relative Predictive Accuracy: A Critical Viewpoint
Tests for relative predictive accuracy have become a widespread addendum to forecast comparisons. Many empirical research reports conclude that the difference between the entertained forecasting models is 'insignificant'. This paper collects arguments that cast doubt on the usefulness of relative predictive accuracy tests. The main point is not that test power is too low but that their application is conceptually mistaken. The features are highlighted by means of some Monte Carlo experiments for simple time-series decision problems.
|Date of creation:||May 2003|
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- Tashman, Leonard J., 2000. "Out-of-sample tests of forecasting accuracy: an analysis and review," International Journal of Forecasting, Elsevier, vol. 16(4), pages 437-450.
- Diebold, Francis X & Mariano, Roberto S, 2002.
"Comparing Predictive Accuracy,"
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American Statistical Association, vol. 20(1), pages 134-44, January.
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- Robert Kunst, 1997. "Augmented ARCH models for financial time series: stability conditions and empirical evidence," Applied Financial Economics, Taylor & Francis Journals, vol. 7(6), pages 575-586.
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