Forecasting the cost of quotes using LSTM & GRU networks
Roman Sergeevich Ekhlakov, Vladimir Anatolievich Sudakov · Keldysh Institute Preprints · 2022
The paper considers modern recurrent neural networks (RNN). Most attention is paid to popular and powerful architectures – long chain of elements of short-term memory (LSTM) and controlled recurrent units (GRU). A software package for forecasting the cost of quotations has been written and a comparison of two methods has been made.