In the present work, an analysis objective is proposed under a statistical model that allows estimating the prices of the shares of the Dow Jones index (DJI); New York Stock Exchange-owned index comprised of 30 of the most significant stocks in all industries except publicly traded transportation and utilities. The estimate and the corresponding statistical analysis are made based on historical information from the period January 1, 2019 to January 1, 2022; using statistical inference from the point of view of time series with tools such as ARIMA and application of the neural network model to subsequently compare these proposals and thus select the most accurate model and its descriptive analysis of the DJI target variable.