证券市场灰色神经网络组合预测模型应用研究
谭华[1] 谢赤[1,2] 孙柏[1] 储慧斌[2] 闫瑞增[1]
[1]湖南大学工商管理学院,湖南长沙410082 [2]湖南大学金融与投资管理研究中心,湖南长沙410082
摘 要:
提出将3种灰色模型(残差GM(1,1),无偏GM(1,1)和pGM(1,1))与神经网络模型进行有机组合,建立一种新的灰色神经网络组合预测模型,并以中国股票市场上证指数为例进行模拟预测.实证表明:组合预测模型的模拟预测精度较原有方法更为精确,可作为股市预测的有效工具.[著者文摘]
文章出处:
《湖南大学学报:自然科学版》-2007年34卷9期 -86-89页
栏目信息:
分 类 号:
文献标识码:
A
文章编号:
1000-2472(2007)09-0086-04
Combination Forecasting Model of Securities Market Based on Grey Model and Neural Network
TAN Hua, XIE Chi, SUN Bo , CHU Hui-bin, YAN Rui-zeng ( 1. College of Business Administration, Hunan Univ, Changsha, Hunan 410082, China; 2. Center of Finance and Investment Management, Hunan Univ, Changsha,Hunan 410082, China)
Abstract:
Three grey models (residual GM ( 1,1 ), unbiased GM( 1, 1 ), pGM( 1,1 )) and neural network were combined to propose a new combination forecasting model for forecasting on Composite Stock Price Index of the stock market in Shanghai, China. The results show that this model can gain optimized forecasting value and can be taken as an effective tool to predict Shares Price Composite Index.[著者文摘]
Key words:
neural networks; grey model; grey neural network; combination forecasting model; securities market
基金资助:
全国高校青年教师奖励基金资助项目(教人司2002[123]);国家社会科学基金资助项目(03BJY099);教育部博士点专项科研基金资助项目(20020532005)

学术















cqvip.com