沪深300指数预测--基于ARIMA模型、BP神经网络及其组合模型
SI 300 Index forecast--based on ARIMA Model, BP Neural Network model and combined model
作为能够综合反映股票市场变动情况的沪深300指数，在金融市场中发挥着重要的作用。本文用ARIMA模型和BP神经网络和基于熵值法确定的BP-ARIMA组合模型的三种方法对2019年1月~7月的沪深300指数进行实证研究和预测，并通过比较三种模型的平均绝对误差和平均相对误差，判断模型预测效果。结果表明，BP-ARIMA组合模型预测效果最优。
As a CSI 300 index that can comprehensively reflect changes in the stock market, it plays an important role in the financial market. In this paper, the ARIMA model and BP neural network and BP-ARIMA combination model are used to predict the CSI 300 indices from January to July 2019, and the average absolute error and average relative error of the three models are compared. The model predicts the results, and the results show that the BP-ARIMA combined model has the best prediction effect.
胡妍、柳向东
财政、金融自动化技术经济计算技术、计算机技术
沪深300指数RIMA模型BP神经网络组合模型熵值法
SI 300 IndexARIMA modelBP neural networkombined modelEnproty
胡妍,柳向东.沪深300指数预测--基于ARIMA模型、BP神经网络及其组合模型[EB/OL].(2019-09-30)[2025-08-02].http://www.paper.edu.cn/releasepaper/content/201909-70.点此复制
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