Integration of the Russian Stock Market with Systems of Artificial Neural Network and Their Applications

Humanity is at the door of the new dimension of infinite possibilities in terms of knowledge, scientific-technical advances, neuroscience, and self-knowledge of the human being. Such topics as artificial intelligence, digital economy, and artificial neural networks are increasingly recurring. The authors propose to model a large system of neural networks to integrate and control all Russian stock markets. This model will be able to predict, decide, and execute operations, increasing the rate of response in each operation and decreasing the margin of error in those operations, and in which constant monitoring of man will no longer be necessary. The model will be very flexible in its structure, allowing the integration of several similar systems. Such a structure will also ensure the interconnection between them, contributing to the achievement of a fully automated and sustainable stock market for the sake of economic integration. The article provides a theoretical basis for further research for practical purposes. This first part explains the basic concepts and models currently in place to predict some stock market behavior. © 2021, Springer Nature Switzerland AG.

Авторы
Сборник материалов конференции
Издательство
Springer Science and Business Media Deutschland GmbH
Язык
Английский
Страницы
645-654
Статус
Опубликовано
Том
280
Год
2021
Организации
  • 1 Peoples’ Friendship University of Russia (RUDN University), Moscow, Russian Federation
  • 2 Plekhanov Russian University of Economics, Moscow, Russian Federation
Ключевые слова
Artificial intelligence; Artificial neural network; Russian stock markets
Дата создания
16.12.2021
Дата изменения
16.12.2021
Постоянная ссылка
https://repository.rudn.ru/ru/records/article/record/76250/
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