Peer-Reviewed Article January 23, 2018
Non-linear Autoregressive with Exogeneous input (narx) bitcoin price prediction model using PSO-optimized parameters and moving average technical indicators
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Published in: Journal of Fundamental and Applied Sciences
Publisher: El Oued University • Algeria • 1112-9867
Abstract
This paper presents a Multi-Layer Exogeneous Inputs (NARX) Bitcoin price forecasting model using the opening, closing, minimum and maximum past prices together with Moving Average (MA) technical indicators.As there were many parameter (PSO)-based method was used to optimize the number of hidden units, input lag and output lag of the NARX model.The results demonstrated the ability of the model to predict Bitcoin prices accurately while passing all model validation tests.