We analyse the properties of the Diebold and Mariano (1995) test in the presence of autocorrelation in the loss differential. We show that the power of the Diebold and Mariano (1995) test decreases as the dependence increases, making it more difficult to obtain statistically significant evidence of superior predictive ability against less accurate benchmarks. We also find that, after a certain threshold, the test has no power and the correct null hypothesis is spuriously rejected. Taken together, these results caution to seriously consider the dependence properties of the loss differential before the application of the Diebold and Mariano (1995) test.
Testing for equal predictive accuracy with strong dependence / L. Coroneo, F. Iacone. - In: INTERNATIONAL JOURNAL OF FORECASTING. - ISSN 0169-2070. - (2025), pp. 1-20. [Epub ahead of print] [10.1016/j.ijforecast.2024.11.003]
Testing for equal predictive accuracy with strong dependence
F. Iacone
Ultimo
2025
Abstract
We analyse the properties of the Diebold and Mariano (1995) test in the presence of autocorrelation in the loss differential. We show that the power of the Diebold and Mariano (1995) test decreases as the dependence increases, making it more difficult to obtain statistically significant evidence of superior predictive ability against less accurate benchmarks. We also find that, after a certain threshold, the test has no power and the correct null hypothesis is spuriously rejected. Taken together, these results caution to seriously consider the dependence properties of the loss differential before the application of the Diebold and Mariano (1995) test.File | Dimensione | Formato | |
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