APPLICATION OF NEURAL NETWORK FOR FORECASTING OF EXCHANGE RATES AND FOREX TRADING

Nijolė Maknickienė; Algirdas Maknickas;

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ABSTRACT

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 in- formation processing techniques - Delphi method and prediction compatibility. Proposed algorithm lim- ited 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 in- crease of the reliability of prediction. Developed algorithm was applied for trading of historical forex ex- change rates. Obtained test trading results were presented

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