BP算法和对称ARCH类模型对股市波动性预测的实证比较

庞素琳; 徐建闽; 黎荣舟

引用本文:	庞素琳,徐建闽,黎荣舟.BP算法和对称ARCH类模型对股市波动性预测的实证比较[J].控制理论与应用,2006,23(4):658~662.[点击复制]
	PANG Su-lin, XU Jian-min, LI Rong-zhou .Comparison:the volatility forecasting of BP algorithm and symmetric ARCH model to stock market[J].Control Theory and Technology,2006,23(4):658~662.[点击复制]

BP算法和对称ARCH类模型对股市波动性预测的实证比较

Comparison:the volatility forecasting of BP algorithm and symmetric ARCH model to stock market

摘要点击 1728 全文点击 723 投稿时间：2004-09-14 修订日期：2005-12-21

查看全文查看/发表评论下载PDF阅读器

DOI编号

2006,23(4):658-662

中文关键词 BP算法 ARCH(1)模型 GARCH(1,1)模型波动性

英文关键词 BP algorithm ARCH(1) model GARCH(1,1) model volatility

基金项目国家自然科学基金资助项目(60574069); 广东省自然科学基金资助项目(31906); 广东省科技厅攻关项目(2004B10101033); 广州市科技局攻关项目(2004Z3-D0231); 广东省软科学研究项目(2005B70101044)

作者	单位
庞素琳,徐建闽,黎荣舟	暨南大学数学系,广东广州510632 华南理工大学交通学院,广东广州510640

中文摘要

利用我国深圳股票市场的实际数据,建立了相应的BP算法网络预测模型和ARCH(1),GARCH(1,1)预测模型,分别用来对深成指数每个周末收盘价的波动性进行预测．研究表明,BP算法对样本外观测值的上凸曲线拟合得较好,对下凸曲线的拟合效果较差;ARCH(1)和GARCH(1,1)则反之,其预测曲线对样本外观测值的下凸曲线拟合效果都较好,但对上凸曲线的拟合效果都较差．通过采用6种常用的预测误差统计量:平均误差、平均绝对误差、均方根误差、平均绝对比率误差、Akaike信息准则、Baves信息准则对样本外数据的预测结果进行检验,BP算法的预测效果最好,ARCH(1)模型次之,GARcH(1,1)模型偏差．

英文摘要

Three forecasting models, called BP algorithm, ARCH(1) and GARCH(1,1), are established based on the actual data of Shenzhen stock market, China. The proposed three models are respectively used to predict the volatility of the weekly closing price of the composition indexes in Shenzhen Stock Exchange. Furthermore, six common statistical methods of the forecasting error, i.e., mean error (ME), mean absolute error (MAE), root mean squared error (RMSE), mean absolute percentage error (MAPE), Akaike's information criterion (AIC) and Bayesian information criterion (BIC) are used to test the forecasting results of the out-of-sample data. The results show that the forecasting result of BP algorithm is the best, the ARCH(1) model takes the second place and the GARCH(1,1) model is the worst.