Compara mètodes

	Test de Diebold-Mariano de Precisió Predictiva Equivalent	Model Confidence Set
Camp	Econometria	Econometria
Família	Hypothesis test	Hypothesis test
Any d'origen	1995	2011
Autor original	Francis Diebold & Roberto Mariano	Hansen, Lunde & Nason
Tipus	Non-parametric forecast comparison test	Sequential hypothesis testing procedure for model comparison
Font seminal	Diebold, F. X., & Mariano, R. S. (1995). Comparing predictive accuracy. Journal of Business & Economic Statistics, 13(3), 253–263.	Hansen, P. R., Lunde, A., & Nason, J. M. (2011). The model confidence set. Econometrica, 79(2), 453–497.
Àlies	DM Test, Test of Equal Forecast Accuracy, Diebold-Mariano Forecast Comparison Test, Tahmin Doğruluğu Eşitliği Testi	MCS Procedure, Superior Set of Models, Model Selection Confidence Set, Model Güven Kümesi
Relacionats	3	3
Resum	The Diebold-Mariano (DM) test, introduced by Diebold and Mariano in 1995, is a widely used non-parametric procedure for formally comparing the predictive accuracy of two competing forecasting models. It evaluates whether the difference in forecast errors between two models is statistically significant, without requiring nested models or specific distributional assumptions about the forecasts, making it broadly applicable across economics, finance, and time-series analysis.	The Model Confidence Set (MCS) is a sequential hypothesis-testing procedure introduced by Hansen, Lunde, and Nason (2011) that identifies the smallest collection of forecasting or predictive models statistically indistinguishable from the best-performing model at a given confidence level. Instead of selecting a single winner, MCS returns a set of superior models, making it especially valuable in econometric forecast comparisons where the true best model is unknown.