Volatility forecasting with an extended GARCH-MIDAS approach

被引:3
|
作者
Li, Xiongying [1 ]
Ye, Cheng [1 ]
Bhuiyan, Miraj Ahmed [1 ,2 ]
Huang, Shuiren [1 ]
机构
[1] Guangdong Univ Finance & Econ, Sch Econ, Guangzhou, Peoples R China
[2] Guangdong Univ Finance & Econ, Sch Econ, Guangzhou 510320, Peoples R China
关键词
GARCH-MIDAS; MCS inspection; uncertainty index; volatility forecasting; ECONOMIC-POLICY UNCERTAINTY; STOCK-MARKET VOLATILITY; GEOPOLITICAL RISKS; TERRORIST ATTACKS; COMPANIES EVIDENCE; RETURNS; IMPACT; DYNAMICS; CHINESE; PRICES;
D O I
10.1002/for.3023
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper uses the generalized autoregressive conditional heteroscedasticity mixing data sampling (GARCH-MIDAS) model to construct three types of extended models. Geopolitical risk uncertainty is included in the study as an introduced variable, and its impact on the Shanghai Stock Exchange (SSE) 50 index volatility is analyzed. The empirical analysis shows that the GARCH-MIDAS-RV-EPU model with China's EPU is the best in predicting the volatility of China's stock market when the information of economic policy uncertainty (EPU) and geopolitical risk uncertainty (GPR) of other countries are included. When the common information model composed of China's economic policy uncertainty index and geopolitical uncertainty index is used to predict the volatility of the SSE, the model's prediction is better. Finally, when the model confidence set (MCS) and the interval length index that changes the forecast outside the sample are used to retest each conclusion, the results are very robust.
引用
收藏
页码:24 / 39
页数:16
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