  This paper introduces FlexCodeTS, a new conditional density estimator for
time series. FlexCodeTS is a flexible nonparametric conditional density
estimator, which can be based on an arbitrary regression method. It is shown
that FlexCodeTS inherits the rate of convergence of the chosen regression
method. Hence, FlexCodeTS can adapt its convergence by employing the regression
method that best fits the structure of data. From an empirical perspective,
FlexCodeTS is compared to NNKCDE and GARCH in both simulated and real data.
FlexCodeTS is shown to generally obtain the best performance among the selected
methods according to either the CDE loss or the pinball loss.
