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This study investigates the performance of a novel neural network technique in the problem of price forecasting. To improve the prediction accuracy using each model's unique features, this research proposes a hybrid approach that combines the -factor GARMA process, empirical wavelet transform and the local linear wavelet neural network (LLWNN) methods, to form the GARMA-WLLWNN process. In order to verify the validity of the model and the algorithm, the performance of the proposed model isdoi:10.15173/esr.v24i1.4135 fatcat:qjppz6be3zdibnvd47newdftiy