We discuss the applications of random matrix theory in the context of Financial markets and econometric models, a topic about which a considerable number of papers have been devoted to in the last decade. We intended to briefly review various theoretical results, old ones (the Marcenko-Pastur spectrum and its various generalizations) and newer ones (random singular value decomposition, eigenvector dynamics) as well as some concrete applications to portfolio optimization and out-of-sample risk estimation.