基于ARIMA和LSTM的上证指数预测与分析

Prediction and analysis of SSE Index Based on ARIMA and LSTM

近年来,股票已成为很多普通人的投资对象。而上证指数作为股市风向标,对于宏观经济和整个股票市场具有十分重要的作用。用机器学习的方法研究上证指数,有助于了解股市变动,掌握上证多数个股的走势,给决策及投资者提供一些建议。基于此,以上证每日指数为研究对象,对2000-2022年的数据进行研究,采用差分自回归移动平均模型(Autoregressive Integrated Moving Average,ARIMA)与长短期记忆(Long Short Term Memory,LSTM)模型拟合上证指数收盘价,然后对预测结果进行分析并做出评价。

In recent years,stocks have become the investment object of many ordinary people.As the wind vane of the stock market,the Shanghai Composite Index plays a very important role in the macro economy and the entire stock market.Using machine learning method to study the SSE Index is helpful to understand the changes in the stock market,grasp the trend of most stocks in the Shanghai Stock Exchange,and provide some suggestions for decision makers and investors.Based on this,taking the daily index of Shanghai Stock Exchange as the research object,the data from 2000 to 2022 is studied,and the closing price of Shanghai Stock Exchange is fitted with the Autoregressive Integrated Moving Average(ARIMA)and Long Short Term Memory(LSTM)models,and then the prediction results are analyzed and evaluated.