On modeling trading strategies for currency pairs using deep neural networks and method of moving separation of mixtures

The paper describes the use of deep neural networks and the method of moving separation of mixtures to construct models for analyzing the foreign exchange market and choosing trading strategies. The architecture of a neural network and methods of statistical extension of the feature space are considered. The results of a trading model demonstrating the advantages of the proposed approach are presented.