基于arima模型的深股指数预测分析
Shenzhen Stock Index Predictive Analysis Based on ARIMA Model

股票是人们进行投资和理财的重要方式。随着我国人民生活水平的改善和提高，股票投资越来越受到人们的关注。对于股票的预测不仅能给投资者带来可观的收益，并且能很大程度上促进国民经济的发展。股票预测主要以预测股票未来的价格走势，帮助人们做出符合最大收益的决策为动力，具有较强的现实意义。本文选取了深股指数2019年12月30日到2022年11月18日的每日收盘指数，对数据进行平稳性检验后判断为非平稳序列。对数据进行差分化处理，再结合自相关性和偏自相关性的知识，结合差分、ACI和模型显著性的相关原则，构建了ARIMA模型，对深股指数进行总结和整体预测，为未来的相关研究提供一定的依据和参考。
Stocks are an important way for people to invest and manage their finances. With the improvement and improvement of the living standards of our people, stock investment has attracted more and more attention. The forecast of stocks can not only bring considerable returns to investors, but also greatly promote the development of the national economy. Stock forecasting is mainly driven by predicting the future price trend of stocks and helping people make decisions that are in line with the greatest returns, which has strong practical significance. In this paper, the daily closing index of the Shenzhen stock index from December 30, 2019 to November 18, 2022 is selected, and the data is judged to be a non-stationary sequence after a stationary test. The data are differentiated, com-bined with the knowledge of autocorrelation and partial autocorrelation, combined with the corre-lation principles of difference, ACI and model significance, the ARIMA model is constructed, which summarizes and predicts the Shenzhen stock index, and provides a certain basis and reference for future related research.