Abstract
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.
Highlights
The study of the dynamics of financial markets today is a rather difficult and urgent task, since the availability of a correct forecast of price changes is the main element of the success of the owner of a financial asset.Currently, automated trading in the financial market is represented by a number of standing and effective advisors for trading
Neural network automated trading systems are actively discussed in many forums and specialized platforms for traders, since with the proper approach, they can function in a wide variety of markets [1, 3, 8]
Given the disadvantages imposed by statistical methods, machine learning methods such as artificial neural networks (ANNs) in combination with heuristic algorithms will be used as an alternative
Summary
The study of the dynamics of financial markets today is a rather difficult and urgent task, since the availability of a correct forecast of price changes is the main element of the success of the owner of a financial asset. The market is changing and automated trading systems (ATS), which could have been profitable yesterday, are already unprofitable today. To solve this problem, so-called advisors based on neural network technologies have recently appeared. The relevance of the research topic is due to the lack of a large number of tested and free neural network automatic telephone exchanges Such technologies have not been sufficiently studied by trading participants, which is explained by the lack of scientific research by specialists in this field, weak interaction of analytical services and, as a result, the prevalence of stereotypes of market behavior based on subjective practical experience and intuition of the participants in the process. The price of paid neural network automatic telephone exchanges ranges from several tens to several thousand dollars, while the source code of the advisor is hidden, it is impossible to trace on the basis of which rules a particular transaction is made, the user can intervene minimally in the trading process by setting the lot size and a number of other key trading parameters
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