Comparar métodos

	Prueba de Precisión Predictiva Direccional de Pesaran-Timmermann	Test de Diebold-Mariano de Exactitud Predictiva Igual	Prueba de Rachas de Wald-Wolfowitz	Test de los signos
Campo	Econometría	Econometría	Estadística	Estadística
Familia	Hypothesis test	Hypothesis test	Hypothesis test	Hypothesis test
Año de origen	1992	1995	1940	1946
Autor original	M. Hashem Pesaran & Allan Timmermann	Francis Diebold & Roberto Mariano	Abraham Wald & Jacob Wolfowitz	W. J. Dixon & A. M. Mood
Tipo	Nonparametric one-sided test	Non-parametric forecast comparison test	Nonparametric randomness test	Nonparametric median test
Fuente seminal	Pesaran, M. H., & Timmermann, A. (1992). A simple nonparametric test of predictive performance. Journal of Business & Economic Statistics, 10(4), 461–465.	Diebold, F. X., & Mariano, R. S. (1995). Comparing predictive accuracy. Journal of Business & Economic Statistics, 13(3), 253–263.	Wald, A. & Wolfowitz, J. (1940). On a test whether two samples are from the same population. Annals of Mathematical Statistics, 11(2), 147–162.	Dixon, W. J. & Mood, A. M. (1946). The statistical sign test. Journal of the American Statistical Association, 41(236), 557–566.
Alias	PT Test, Directional Accuracy Test, Nonparametric Predictive Performance Test, Pesaran-Timmermann Yön Testi	DM Test, Test of Equal Forecast Accuracy, Diebold-Mariano Forecast Comparison Test, Tahmin Doğruluğu Eşitliği Testi	Wald-Wolfowitz test, runs test for randomness, Runs Testi (Wald-Wolfowitz)	İşaret Testi (Sign Test), one-sample sign test, paired sign test
Relacionados	3	3	5	4
Resumen	Introduced by Pesaran and Timmermann (1992), the PT test is a nonparametric procedure that evaluates whether a forecasting model correctly predicts the direction (sign) of a target variable more often than would be expected by chance. It is widely used in financial econometrics and macroeconomic forecasting to assess the practical utility of a model beyond simple error metrics, particularly when the economic cost of getting the direction wrong is high.	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 Wald-Wolfowitz runs test is a nonparametric hypothesis test that determines whether a sequence of observations — coded as a series of binary symbols — follows a random pattern or contains systematic structure. Introduced by Abraham Wald and Jacob Wolfowitz in 1940, the test counts the number of uninterrupted runs of identical symbols and asks whether that count is consistent with random arrangement.	The sign test is the simplest nonparametric hypothesis test for deciding whether the median of paired differences — or of a single sample — differs significantly from a hypothesised value. Formalised by W. J. Dixon and A. M. Mood in 1946, it imposes virtually no distributional assumptions and can be applied to any data where individual differences can be classified as positive or negative.