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.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | IEEM 2009 - IEEE International Conference on Industrial Engineering and Engineering Management |
| 页 | 2143-2147 |
| 页数 | 5 |
| DOI | |
| 出版状态 | 已出版 - 2009 |
| 活动 | IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2009 - Hong Kong, 中国 期限: 8 12月 2009 → 11 12月 2009 |
出版系列
| 姓名 | IEEM 2009 - IEEE International Conference on Industrial Engineering and Engineering Management |
|---|
会议
| 会议 | IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2009 |
|---|---|
| 国家/地区 | 中国 |
| 市 | Hong Kong |
| 时期 | 8/12/09 → 11/12/09 |
指纹
探究 'Stock indices analysis based on ARMA-GARCH model' 的科研主题。它们共同构成独一无二的指纹。引用此
Wang, W., Guo, Y., Niu, Z., & Cao, Y. (2009). Stock indices analysis based on ARMA-GARCH model. 在 IEEM 2009 - IEEE International Conference on Industrial Engineering and Engineering Management (页码 2143-2147). 文章 5373131 (IEEM 2009 - IEEE International Conference on Industrial Engineering and Engineering Management). https://doi.org/10.1109/IEEM.2009.5373131