基于三类模型的四大银行股票收益率预测研究
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引用本文:李雄英1, 陈小玲1, 曾凯华2.基于三类模型的四大银行股票收益率预测研究[J].经济数学,2018,(4):21-27
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李雄英1, 陈小玲1, 曾凯华2 (1.广东财经大学 统计与数学学院广东 广州 5103202.广东省技术经济研究发展中心,广东 广州 510070) 
中文摘要:运用时间序列分析的预测方法,对四大银行的股票日对数收益率序列进行拟合与预测分析,分别构建ARMA模型、GARCH模型以及ARMA-GARCH组合模型,通过模型比较,实证分析表明:在拟合效果上,ARMA-GARCH模型的拟合优度优于ARMA模型和GARCH模型;在预测效果上,ARMA模型的预测效果最优,ARMA-GARCH模型次之.
中文关键词:ARMA模型  GARCH模型  ARMA-GARCH模型  模型比较
 
Forecast Research of Stock Return Rate of the Big-Four Chinese Banks Based on Three Models
Abstract:The prediction method of time series analysis was used to fit and predict the daily logarithmic return sequences of China's four big Banks. ARMA model, GARCH model and ARMA - GARCH model were constructed respectively. Through the model comparison, the empirical analysis results show that, in terms of fitting effect, the goodness of fit of ARMA - GARCH model is better than that of ARMA model and GARCH model; and in terms of prediction effect, ARMA model has the best prediction effect, followed by ARMA - GARCH model.
keywords:ARMA model  GARCH model  ARMA-GARCH model  model comparison
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