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Abstract:In this paper, we proposed a new hybrid ARIMA-RNN model to forecast stock price, the model based on moving average filter. This model can not only overcome the volatility problem of a single model, but also avoid the overfitting problem of neural network. We forecast stock price using ARIMA, RNN and ARIMA-RNN respectively, and we compare the value of MAE, MSE and MAPE of each model. We conclude that the hybrid ARIMA-RNN model has the best forecasting result.