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Procyclical volatility in Chinese stock markets

Bruno Deschamps (), Tianlun Fei (), Ying Jiang () and Xiaoquan Liu ()
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Bruno Deschamps: Nottingham University Business School China, University of Nottingham Ningbo China
Tianlun Fei: Nottingham University Business School China, University of Nottingham Ningbo China
Ying Jiang: Nottingham University Business School China, University of Nottingham Ningbo China
Xiaoquan Liu: Nottingham University Business School China, University of Nottingham Ningbo China

Review of Quantitative Finance and Accounting, 2022, vol. 58, issue 3, No 9, 1117-1144

Abstract: Abstract We investigate the macroeconomic determinants of stock market volatility in China using the two-component GARCH-MIDAS model of Engle et al. (Rev Econ Stat 95:776–797, 2013). Our analysis shows that both current macroeconomic conditions and macroeconomic expectations impact the long-term component of stock volatility. Chinese macroeconomic data contain more information about Chinese stock market volatility than US macroeconomic data. We provide strong evidence that the long-term volatility is procyclical and increases with the growth rate of industrial production and retail sales. This finding can be explained by the fact that, in China, the volatility of macroeconomic fundamentals is itself procyclical. Finally, we find that specifications that include macroeconomic variables generate superior stock volatility predictions compared to alternative models that do not contain those variables.

Keywords: GARCH-MIDAS; Volatility; Forecasting; Macroeconomic indicators (search for similar items in EconPapers)
JEL-codes: C58 G15 G17 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11156-021-01020-0

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