Abstract

A random map is a discrete time dynamical system consisting of a collection of transformations which are selected randomly by means of probabilities at each iteration. We prove the existence of absolutely continuous invariant measures for different classes of position dependent random maps under mild conditions. Moreover, we prove that these measures are stable under small stochastic perturbations. We also apply these results to forecasting in financial markets.