Forecasting stock volatility with economic policy uncertainty: A smooth transition GARCH-MIDAS model |
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| Affiliation: | 1. School of Finance, Nanjing University of Finance and Economics, Nanjing, China;2. School of Mathematics, Southwest Jiaotong University, Chengdu, China;1. School of Mathematics and Finance, Anhui Polytechnic University, Wuhu, China;2. Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai, China;3. Data-Driven Management Decision Making Lab, Shanghai Jiao Tong University, Shanghai, China;1. School of Economics, Jiaxing University, Jiaxing 314001, China;2. China-ASEAN Institute of Financcial Cooperation, Guangxi University, Nanning, Guangxi, China;3. School of Economics, Guangxi University, Nanning, Guangxi, China;5. Shenzhen International Graduate School, Tsinghua University, Shenzhen, Guangdong, China;6. Guangxi University of Finance and Economics, Graduate School, Nanning, Guangxi, China;1. Department of Digital Economy, Shanghai University of Finance and Economics, No 777 Guoding Road, Shanghai 200433, China;2. School of Information Management & Engineering, Shanghai University of Finance and Economics, No 777 Guoding Road, Shanghai 200433, China;3. Faculty of Business information, Shanghai Business School, No 123 Fengpu Avenue, Shanghai 201400, China;1. College of Finance, Nanjing Agricultural University, Nanjing 210095, China;2. School of Advanced Agricultural Sciences, Peking University, Beijing 100871, China;3. Business School, Hohai University, Nanjing 211100, China |
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| Abstract: | Given that policy uncertainty shocks in the economic environment can exacerbate financial market volatility and pose financial risks, this paper utilizes a smooth transition version of the GARCH-MIDAS model to investigate the impact of different structural state changes in economic policy uncertainty (EPU) on stock market volatility. The extended model explains the nonlinear effects of the macro variables and the structural break changes in regime transitions. The empirical results confirm that the EPU indicators provide effective prediction information for stock volatility from the in-sample and out-of-sample analyses, which reveals that the smooth transition model provides an effective method for detecting the possible regime changes between stock volatility and macroeconomic uncertainty. Additionally, we further confirm that some category-specific EPU indicators also have strong smooth transition behaviour with respect to stock volatility. More important, our new model provides significant economic value to investors from a utility gain perspective. Overall, the institutional changes present in EPU play a nonnegligible and important role in stock market volatility. Accurate identification of the structural features of financial data helps investors deepen their understanding of the sources of stock market volatility. |
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