Résumé
Two smooth nonparametric conditional median predictors, based on double kernel and local constant kernel methods, are defined for time series. Consistency and asymptotic normality are obtained for both of them. An extension to
pth conditional quantiles is proposed in order to get predictive intervals. A rule-of-thumb selection for the smoothing parameters is developed. We illustrate the technique with a simulated sample and we apply it to a real-data analysis.