世界不确定性指数与中国股市波动率预测研究  

Research on World Uncertainty Index and Volatility Forecast of Chinese Stock Market

作　　者：计玉 王璐[1] 郝建阳 张莉 JI Yu;WANG Lu;HAO Jianyang;ZHANG Li(School of Mathematics,Southwest Jiaotong University,Chengdu 611756,China)

机构地区：[1]西南交通大学数学学院,成都611756

出　　处：《河南科学》2021年第10期1549-1556,共8页Henan Science

基　　金：教育部人文社科基金(17XJCZH002);四川省社科规划项目(SC20TJ004);成都软科学研究项目(2020-RK00-00070-ZF)。

摘　　要：大量研究表明经济、政治等宏观不确定因素对股票市场波动会产生显著性影响.为了研究全球经济政策等不确定因素对上证指数波动率的影响,尝试引入Hites Ahir等提出的世界不确定性指数作为宏观变量,构建新的模型——逻辑平滑转换回归-混频广义条件异方差模型(LSTR-GARCH-MIDAS-X),并对模型进行实证分析.实证结果表明,新模型不仅刻画出世界不确定性指数对上证指数波动的非线性影响,并且与广义自回归条件异方差混频数据抽样(GARCH-MIDAS)模型相比,对上证指数波动率的预测能力更好.A large number of studies have shown that macro-uncertainties such as economy and politics have a significant impact on stock market volatility.In order to study the impact of global economic policies and other uncertainties on the Shanghai Stock Exchange Index volatility,an attempt was made to introduce the World Uncertainty Index proposed by Hites Ahir et al.as a macro variable to construct a new model of smooth conversion regression generalized conditional heteroscedasticity(LSTR-GARCH-MIDAS-X)and empirically analyze the model.The empirical results show that the new model not only depicts the non-linear impact of WUI on the volatility of the Shanghai Stock Exchange Index,but also has a better predictive ability for the volatility of the Shanghai Composite Index than the Generalized Autoregressive Conditional Heteroskedasticity Mixed Data Sampling(GARCH-MIDAS)model.

关 键 词：非线性特征 世界不确定性指数 STR-GARCH-MIDAS-X模型 波动率预测 

分 类 号：F832[经济管理—金融学]