An empirical analysis of China's Shenzhen Composite Index based on ARIMA-GARCH model

Abstract

Since the uncertainty of the stock market will affect the returns of investors, and the China Shenzhen Composite Index can basically reflect the fluctuations of the Chinese stock market, it has certain research significance to take the Shenzhen Composite index as the research object. In this paper, the stock composite price index of Shenzhen Composite Index from April 30, 1991 to May 31, 2023 (considering holidays) is selected as the sample, and the ARIMA (2,1,2) model is fitted after first-order difference for this unstable time series. Aiming at the ARCH effect in the residual series of the model, the GARCH (1,1) model is fitted, and the mean value forecast and volatility forecast of the price index of Shenzhen Composite Index from June to the end of October 2023 are carried out according to the fitted model. The final results show that the fitted model has strong short-term prediction ability, but weak long-term prediction ability. However, in general, the prediction results of ARIMA-GARCH model still have great reference value for Chinese investors.