| 利用PSO对上证指数ARCH模型的实证研究 |
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| 引用本文： | 梅娟,孙俊,须文波.利用PSO对上证指数ARCH模型的实证研究[J].计算机工程与应用,2006,42(32):194-196. |
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| 作者姓名： | 梅娟 孙俊 须文波 |
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| 作者单位： | 江南大学,信息工程学院,江苏,无锡,214122 |
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| 摘 要： | 针对ARCH模型传统估计方法的不足,提出了利用微粒群算法及其改进的算法快速精确的估计ARCH模型的参数,最后利用微粒群算法实证建立了上证指数收益的ARCH模型,并且对以后的情况进行了预测。
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| 关 键 词： | ARCH模型 PSO算法 惯性因子 收缩因子 异方差 |
| 文章编号： | 1002-8331（2006）32-0194-03 |
| 收稿时间： | 2006-01-01 |
| 修稿时间： | 2006-01-01 |
Empirical Study on Stock Return of Shanghai Through ARCH with PSO Algroithm |
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| MEI Juan,SUN Jun,XU Wen-bo.Empirical Study on Stock Return of Shanghai Through ARCH with PSO Algroithm[J].Computer Engineering and Applications,2006,42(32):194-196. |
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| Authors: | MEI Juan SUN Jun XU Wen-bo |
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| Affiliation: | Institute of Information Technology, Southern Yangtze University, Wuxi, Jiangsu 214122, China |
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| Abstract: | Because of the disadvantages of traditional estimating methods of ARCH model,this paper estimates the parameters in ARCH model accurately with particle swarm optimization and its improved approaches.Finally the ARCH model for stock return is established empirically with algorithm and forecast of the return is given. |
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| Keywords: | ARCH model PSO algorithm inertia weight constriction factor heteroskedasticity |
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