Application and analysis of forecasting stock price index based on combination of ARIMA model and BP neural network

被引：0
|
作者：
Du, Yulin [1 ,2 ]
机构：
[1] Fudan Univ, Sch Management, Shanghai 200433, Peoples R China
[2] East China Univ Polit & Sci Law, Dept Finance, Shanghai 201620, Peoples R China
来源：
PROCEEDINGS OF THE 30TH CHINESE CONTROL AND DECISION CONFERENCE (2018 CCDC) | 2018年
关键词：
BP neural network; Shanghai Securities Composition stock index; ARIMA-BP; Foresting;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Stock price index is a barometer of the national economy, which often shows strong nonlinearity because of various factors. It is necessary to use nonlinear models to improve the accuracy of prediction. We predict Shanghai Securities Composition stock index with ARIMA-BP neural network method, and compare the accuracy with the result of single ARIMA model and BP neural network method. We find that the prediction accuracy of ARIMA-BP neural network is better than the BP neural network, BP neural network is better than linear model ARIMA, which confirms the change of stock price index is nonlinear.
引用
收藏
页码：2854 / 2857
页数：4
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