Application of neural network for forecasting of exchange rates and forex trading
Santrauka
Expert methods, which widely applied for human decision making, were employed for neural networks. It was developed an exchange rates prediction and trading algorithm with using of experts information processing techniques - Delphi method and prediction compatibility. Proposed algorithm limited to eight experts. Each of experts represented recurrent neural network, Evolino-based Long Short-Term Memory (LSTM) by using of genetic learning algorithm, EVOlution of recurrent systems with LINear Outputs (EVOLINO). Statistical investigation of offered algorithm shows the significantly increase of the reliability of prediction. Developed algorithm was applied for trading of historical forex exchange rates. Obtained test trading results were presented.