The use of neural networks significantly expands the possibilities of analyzing financial data and improves the quality indicators of the financial market. In article we examine various aspects of working with neural networks and Frame work TensorFlow, such as choosing the type of neural networks, preparing data and analyzing the results. The work was carried out on the real data of the financial instrument Si-6.16 (futures contract on the US dollar rate).

Original languageEnglish
Pages (from-to)513-517
Number of pages5
JournalCEUR Workshop Proceedings
Volume2267
StatePublished - 2018
Event8th International Conference "Distributed Computing and Grid-Technologies in Science and Education", GRID 2018 - Dubna, Russian Federation
Duration: 10 Sep 2018 → 14 Sep 2018

    Research areas

  • Artificial Intelligence, Financial market forecasting, Recurrent neural network (RNN), TensorFlow

    Scopus subject areas

  • Computer Science(all)

ID: 76157557