基于ARIMA-GARCH模型的股票分析与预测——以长城汽车为例

Stock Analysis and Prediction Based on ARIMA-GARCH Model—Taking Great Wall Motor as an Example

本文利用时间序列模型对长城汽车股票的收盘价格进行了短期预测。选取了长城汽车(601633)股票2021年1月4日至2023年3月20日的收盘价作为样本数据,使用R软件建立ARIMA、ARIMA-GARCH模型分别对该股票价格进行预测比较。结果表明,ARIMA、ARIMA-GARCH对股票价格的短期预测都有一定的参考意义,但是对于带有异方差的时间序列,ARIMA-GARCH模型的预测性能更好,说明该模型存在着相应的参考价值和现实意义,ARIMA-GARCH模型可以为一般投资者以及相关投资机构提供股票投资决策参考。

In this paper, the closing price of Great Wall Motor stock is predicted in a short term by using time series model. The closing price of Great Wall Motor (601633) from January 4, 2021 to March 20, 2023 is selected as sample data, and ARIMA and ARIMA-GARCH models are established by using R software to forecast and compare the stock price respectively. The results show that ARIMA and ARIMA-GARCH have certain reference significance for short-term forecasting of stock prices, but ARIMA-GARCH model has better forecasting performance for time series with heteroscedasticity, which shows that the model has certain reference value and practical significance. ARIMA-GARCH model can provide reference for investors and related investment institutions to make stock investment decisions.