Stock Indices Analysis Based on ARMA-GARCH Model

被引：2
|
作者：
Wang, Weiqiang [1 ]
Guo, Ying [2 ]
Niu, Zhendong [1 ]
Cao, Yujuan [1 ]
机构：
[1] Beijing Inst Technol, Sch Comp Sci, Beijing 100081, Peoples R China
[2] Beijing Inst Technol, Sch Management & Econ, Beijing, Peoples R China
来源：
2009 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT, VOLS 1-4 | 2009年
关键词：
ARMA-GARCH model; time series; DOW; S&P 500;
D O I：
10.1109/IEEM.2009.5373131
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The generalized autoregressive conditional heteroskedasticity (GARCH) model has become the most popular choice in the analysis of time series datas. In this paper, an autoregressive moving average (ARMA) - GARCH model was built, and it also provided parameter estimation, diagnostic checking procedures to model, and predict Dow and S&P 500 indices data from 1988 to 2008,which extracted from yahoo website, and also compared with the GARCH conventional model, experimental results with both two data sets indicated that this model can be an effective way in financial area.
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页码：2143 / +
页数：2
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