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.
机构:
Ctr Econometr & Appl Res, Ibadan, Nigeria
Univ Econ Ho Chi Minh City, Inst Business Res, Ho Chi Minh City, VietnamCtr Econometr & Appl Res, Ibadan, Nigeria
Salisu, Afees A.
Penzin, Dinci J.
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Cent Bank Nigeria, Res Dept, Abuja, NigeriaCtr Econometr & Appl Res, Ibadan, Nigeria
Penzin, Dinci J.
Vo, Xuan Vinh
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Univ Econ Ho Chi Minh City, Inst Business Res & CFVG Ho Chi Minh City, Ho Chi Minh City, VietnamCtr Econometr & Appl Res, Ibadan, Nigeria
机构:
Univ Ibadan, Dept Stat, Econ & Financial Stat Unit, Ibadan, Nigeria
Univ Econ Ho Chi Minh City, Inst Business Res, Ho Chi Minh City, VietnamUniv Ibadan, Dept Stat, Econ & Financial Stat Unit, Ibadan, Nigeria
Yaya, OlaOluwa S.
Ogbonna, Ahamuefula E.
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Univ Ibadan, Dept Stat, Econ & Financial Stat Unit, Ibadan, Nigeria
Ctr Econometr & Appl Res, Ibadan, NigeriaUniv Ibadan, Dept Stat, Econ & Financial Stat Unit, Ibadan, Nigeria
Ogbonna, Ahamuefula E.
Xuan Vinh Vo
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Univ Econ Ho Chi Minh City, Inst Business Res, Ho Chi Minh City, VietnamUniv Ibadan, Dept Stat, Econ & Financial Stat Unit, Ibadan, Nigeria