In recent years, we are witnessing the incredible development of artificial intelligence and its sub-types such as machine learning and deep learning. For the first time in history, access to data and technological development enable the effective application of artificial intelligence in a variety of fields, from self-driving cars to virtual assistants, warehouse robots (eg. Alibaba), production lane robots, and the like. The development of the Internet has encouraged the development of various technologies that have allowed artificial intelligence to „jump“ from theoretical models to practical ones, including: data mining, development of programming languages (eg. Python) and code libraries, various business intelligence tools, etc. Today, we can build artificial neural networks (deep learning) easily and quickly, and apply them to a variety of analyses and tasks, which have allowed deep learning to constantly find new areas where they optimize processes, reduce costs and drive innovation. One of these areas is the securities market, where deep learning is used for various analyses, trend recognition and forecasting, and the development of neural networks in this area along with recent technological successes are an incentive for further research and deeper application of deep learning methods to securities market.