ПРОГРАМНІ РІШЕННЯ ДЛЯ ДОПОВНЕННЯ ТРЕЙДИНГОВОЇ ТОРГІВЛІ

The purpose of this work is to study and evaluate various methods and technologies applicable for the development of trading forecasting systems in the stock market. It examines the different types of neural networks suitable for solving such problems, existing implementations and strategies for improving software solutions, and the possibility of combining their use with conventional algorithmic trading methods. By combining different approaches, it is possible to improve the efficiency of the system as a whole, since it is not always possible to ensure optimal operation of systems using neural networks due to the specifics of time series and factors that may not be taken into account during modeling, in this case, solutions using trading algorithms can save the system from excess losses.