基于时间序列模型的上证A股指数实证分析

Empirical Analysis of Shanghai A Shares Index Based on Time Series Model

选取20172021年上证A股指数,运用R语言和EVIEWS软件,拟建了ARIMA模型及GARCH簇模型,并进行短期估测,筛选出最佳模型——ARIMA-EGARCH综合模型。通过综合分析水平与波动两方面,得出上证A股指数是非平稳的,差分序列的偏自相关系数明显拖尾,ARIMA(2,1,2)模型残差序列存在异方差性,上证A股指数未遭受风险的显著影响。为改善我国股市环境,有效规避股市风险,提出了相关建议。

The study selects Shanghai Stock Exchange A shares index from 2017 to 2021,applies R language and EVIEWS software,proposes ARIMA model and GARCH cluster model,makes short-term prediction,and selects optimal model:ARIMA-EGARCH comprehensive model.Through the comprehensive analysis of two aspects:level and fluctuation,Shanghai Stock Exchange A shares index are unstable,the partial autocorrelation coefficient of difference sequence is obviously trailing.There is difference in residual sequence in ARIMA(2,1,2)model.There is no significant influence of Shanghai A shares index.Related suggestions are proposed to improve China’s stock market environment,and effectively avoid stock risk.