E3S Web Conf.
Volume 224, 2020Topical Problems of Agriculture, Civil and Environmental Engineering (TPACEE 2020)
|Number of page(s)||5|
|Section||Mathematical Models for Environmental Monitoring and Assessment|
|Published online||23 December 2020|
Machine learning for algorithmic trading
Don State Technical University, Rostov-on-Don, 344000, Russia
* Corresponding author: email@example.com
The purpose of the study is to confirm the feasibility of using machine learning methods to predict the behavior of the foreign exchange market. The article examines the theoretical and practical aspects of the implementation of artificial neural networks in the process of Internet trading. We studied the features of constructing automated trading advisors that perform trading operations based on the forecast of neural networks in combination with indicator signals. As a result, a hybrid system has been built that has a high-precision forecast and allows you to make a profit with the correct selection of parameters.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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