Prediction of univariate financial series

Time series prediction has been the subject of a considerable number of studies due to the innumerable amounts of temporal and sequential data produced daily by the information industry and various research structures. This field has undergone a spectacular effervescence and has continued to grow in recent years with the explosion of digital data, Big Data and especially artificial intelligence. This book represents a technical introduction to the different methods of predicting univariate chronicles on financial markets with empirical applications, while mobilizing two families of completely distinct approaches, a first one based on econometric models and a second one based on machine learning by recurrent artificial neural networks.