Hybrid model "arima-ann" using for forecasting stock index egx30

الملخص EN

This research aims to evaluate the efficiency of hybrid model ARIMA-ANN in forecasting by stock market index EGX30 since 3 / 1 / 2022 to 9 / 1 / 2022.

in this research discussion three models which are autoregressive integrated moving average (ARIMA), artificial neural network (ANN) and the hybrid model (ARIMA-ANN), while ARIMA (0, 1, 1) has been used to estimate the linear part of model, then estimating the non- linear part of model by the difference between actual data and estimated data of series, so the model of ANN (2, 5, 1) has been used to estimate the non-linear part of the model and by collecting the two parts for getting finally the hybrid model for forecasting processing, after comparing three models and based on standard group such as mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE),we achieved that “the hybrid model (ARIMA-ANN) was the best model in forecasting by stock index EGX30 and it is better than ARIMA (0, 1, 1) and ANN (2, 5, 1) which did singularly, that is because hybrid model has the minimum accurately values of forecasting standards.