[1]吴朝阳.改进的灰色模型与ARMA模型的股指预测[J].智能系统学报,2010,5(03):277-281.
 WU Zhao-yang.Forecasting stock indexes based on a revised grey model and the ARMA model[J].CAAI Transactions on Intelligent Systems,2010,5(03):277-281.
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改进的灰色模型与ARMA模型的股指预测(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第5卷
期数:
2010年03期
页码:
277-281
栏目:
出版日期:
2010-06-25

文章信息/Info

Title:
Forecasting stock indexes based on a revised grey model and the ARMA model
文章编号:
1673-4785(2010)03-0277-05
作者:
吴朝阳
康考迪亚大学 统计与数学系,蒙特利尔 H3G 2H9
Author(s):
WU Zhao-yang
The Department of Mathematics and Statistics, Concordia University, Montreal H3G 2H9, Canada
关键词:
灰色模型GM(11)模型ARMA模型GMARMA模型股指预测
Keywords:
grey model GM (1 1) model ARMA model GMARMA model stock prediction
分类号:
TP18
文献标志码:
A
摘要:
当前基于灰色GM(1,1)模型和ARMA模型的组合模型GMARMA模型存在着2点不足:一是由于GM(1,1)模型不是最优的,导致了GMARMA模型也不是最优的;二是GMARMA模型并没有恰当地结合2个子模型,这也导致了GMARMA模型不是最优的. 为此,首先引入数据维度参数和白化背景值的系数2个参数来改进GM(1,1)模型,然后同时优化ARMA模型中的P、Q 2个参数来改进GMARMA模型, 称新的模型为Revised GMARMA(RGMARMA)模型.实例证明RGMARMA的误差小于ARIMA和GMARMA模型,并且为组合模型的建立提供了新的思路.
Abstract:
A hybrid grey model—autoregressive moving average (GMARMA) model, constructed by combing the GM (1, 1) model and the ARMA model, has two drawbacks. One drawback is that the GMARMA model may not be optimal since the traditional GM (1, 1) model is not optimal. The other is that the GMARMA model does not combine two submodels properly; this may also cause the GMARMA model to be suboptimal. This paper tries to first modify the GM (1, 1) model by introducing 2 parameters, the grey dimension degree and white background value. A revised GMARMA model was constructed by optimizing all parameters in the GM (1, 1) model and the ARMA model simultaneously. For convenience, we called this revised GMARMA model the RGMARMA model. Experimental results showed that the RGMARMA model has fewer prediction errors than the ARMA model or the GMARMA model and gives a new solution for construction of hybrid models. 

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备注/Memo

备注/Memo:
收稿日期:2009-11-22.
通信作者:吴朝阳.
E-mail:hostingca@gmail.com.
作者简介:吴朝阳,男,1975年生,工程师,主要研究方向为灰色理论、时间序列和小波变换的股票预测.
更新日期/Last Update: 2010-08-27