Statistical Tests for Multiple Forecast Comparison
16 Pages Posted: 15 Aug 2012
Date Written: August 14, 2012
Abstract
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 T-square or bootstrap critical values.
Keywords: forecast comparison, multivariate tests of equal predictive ability, Diebold–Mariano test, finite-sample correction
Suggested Citation: Suggested Citation
Do you have a job opening that you would like to promote on SSRN?
Recommended Papers
-
Tests of Equal Forecast Accuracy and Encompassing for Nested Models
-
Long Swings in the Exchange Rate: are They in the Data and Do Markets Know it?
-
Exchange Rates and Fundamentals
By Charles M. Engel and Kenneth D. West
-
Exchange Rates and Fundamentals
By Charles M. Engel and Kenneth D. West
-
Empirical Exchange Rate Models of the Nineties: Are Any Fit to Survive?
By Menzie David Chinn, Yin-wong Cheung, ...
-
Exchange Rates and Monetary Fundamentals: What Do We Learn from Long-Horizon Regressions?
By Lutz Kilian
-
Empirical Exchange Rate Models of the Nineties: Are Any Fit to Survive?
By Yin-wong Cheung, Menzie David Chinn, ...