Convergence in distribution for the sup-norm of a kernel density estimator for GARCH innovations

The estimation and identification of the GARCH innovation density is an important task, leading to efficient parameter estimation. In this paper we derive the asymptotic distribution for the sup-norm of a kernel density estimator, and presents a goodness-of-fit test for the innovation density.