Statistical tests for multiple forecast comparison

By Roberto S. Mariano, Daniel P. A. Preve. 2012

70 citations recorded by the source corpus.

We consider a multivariate version of the Diebold–Mariano test for equal predictive ability of three or more forecasting models. The Wald-type test, S, which has a null distribution that is asymptotically chi-squared, is shown to be generally invariant with respect to the ordering of the models being compared. Finite-sample corrections for the test are also developed. Monte Carlo simulations indicate that S has reasonable size properties in large samples but tends to be oversized in moderate samples. The finite-sample correction succeeds in correcting for size, but only partially. For the size-adjusted tests, power increases with sample size, as expected. It is speculated that further finite-sample improvements can be achieved using Hotelling’s T2 or bootstrap critical values.

Subfields: Economics and Econometrics, Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/2383f11ba6ff9bd1694256209ea8e51cead68269

Citations in the corpus

• Advances in Forecast Evaluation (2011, unknown): “Granziera, Hubrich, and Moon (2011) propose a likelihood ratio-type predictability test 20 In another recent extension for non-nested models, Mariano and Preve (2012) propose a multivariate version of the Diebold and Mariano (1995) test for application to forecasts that either do not come from…”