Securities market forecasting using machine learning methods

The article deals with the use of machine learning methods for forecasting the securities market. Particular attention is paid to the description of the neural network architecture, in particular the LSTM network (Long Short-Term Memory), which most effectively solves the problem of predicting prices for financial assets. A scheme of the financial market forecasting process using LSTM network is presented. The article also discusses the prospects of the model development, including consideration of geopolitical situations, currency fluctuations and natural factors.