基于灰色GARCH模型和BP神经网络的股票价格预测  

Stock Price Forecasting Based on Grey GARCH Model and BP Neural Network

作　　者：曹晓 孙红兵[1] CAO Xiao;SUN Hong-bing(Kunming University of Science and Technology, College of Science, Kunming 650500, China)

机构地区：[1]昆明理工大学理学院,云南昆明650500

出　　处：《软件》2017年第11期126-131,共6页Software

摘　　要：针对传统算法进行股票价格预测存在预测精度低和滞后性大的缺点,提出一种基于灰色GARCH模型和BP神经网络的股票价格预测模型。通过BP神经网络校正灰色GARCH模型预测残差实现股票价格的高精度预测。研究结果表明,与灰色GARCH、BP、GARCH和灰色模型相比较,本文提出的灰色GARCH-BP组合模型可以有效提高股票价格预测精度,为股票价格预测提供新的方法和途径。In view of the traditional algorithm to predict stock price the shortcomings of low precision and big lag,put forward a GARCH model based on gray prediction model of stock price and the BP neural network.By the BP neural network correction grey GARCH model to predict residual stock price the high precision of prediction.Research results show that with the gray GARCH,BP,GARCH and grey model,this paper puts forward the grey GARCH-BP combination model can effectively improve the predictive accuracy of the stock price for the stock price forecast provide new ways and means.

关 键 词：灰色GARCH模型 GARCH模型 BP神经网络 股票价格 

分 类 号：F83[经济管理—金融学]