SSEC Forecast Based on ARIMA and ETS Models

Stock price forecasting is the main concern of the financial industry, which is affected by many macroeconomic variables. The Shanghai Securities Composite Index (SSEC), as a representative index of the Chinese stock market, provides an overall overview of the performance of the Chinese capital market. China's economic policy changes, especially the adjustment of monetary policy, have had a significant impact on the stock market. In this paper, ARIMA and ETS models are used to forecast SSEC under the current macroeconomic environment. The results show that the root mean square error (RMSE) value of ETS model is lower than that of ARIMA model, indicating that ETS model is more accurate in SSEC prediction. In addition, the ETS model is particularly suitable for stock market forecasting due to its ability to account for exponential trends. In order to provide a new perspective for predicting the Shanghai Stock Composite Index and provide guidance for stock market forecasting under complex economic environment, the ARIMA and ETS models are analyzed in this study.