Economic policy uncertainty and stock market activity: Evidence from China

Lei, Adrian C. H.; Song, Chen

doi:10.1016/j.gfj.2020.100581

Cited by 11 publications

(8 citation statements)

References 34 publications

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“…Urban economic growth was severely affected by the delayed return of workers to jobs in the city under the impact of the pandemic—a large number of enterprises shut down or reduced production, there was a significant reduction in the transportation activities of industrial manufacturing goods and production-oriented raw materials, and a basic stagnation of short-term development in certain manufacturing and infrastructure investment activities set in. Simultaneously, foreign economic policies toward China became highly uncertain due to the pandemic, which in turn has continued to affect China's economic performance ( Kong, Peng, Ni, Jiang, & Wang, 2020 ; Lei & Song, 2020 ). Foreign policy shocks may affect China's factor markets, financial markets, and the investment behavior of its firms ( Zhang, Guo, Wang, & Chen, 2020 ; Kong, Guo, Wang, Sui, & Zhou, 2020 ; Kong, Tong, Peng, Wong, & Chen, 2021 ), while free trade can improve the overall information efficiency of financial markets ( Baig, Blau, & Sabah, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

High-speed railway opening and urban green productivity in the post-COVID-19: Evidence from green finance

Kong

Shen

et al. 2021

Global Finance Journal

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Section: Introductionmentioning

confidence: 99%

High-speed railway opening and urban green productivity in the post-COVID-19: Evidence from green finance

Kong

Shen

et al. 2021

Global Finance Journal

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“…It was observed that uncertainty indices explained changes in different economic and financial variables quite well. Upon reviewing studies in the literature, it is observed that it significantly explains changes in variables such as financial markets (Liu & Zhang, 2015; Chen, Jiang, & Tong, 2017; Debata & Mahakud, 2018; Lei & Song, 2020; Batabyal & Killins, 2021; Chang, 2022), investments (Kang, Lee, & Ratti, 2014; Wang, Chen, & Huang, 2014; Drobetz, Ghoul, Guedhami, & Janzen, 2018; Choi, Furceri, & Yoon, 2021; Nguyen & Lee, 2021; Qamruzzaman, Karim, & Jahan, 2022) and exchange rates (Krol, 2014; Bartsch, 2019; Liming, Ziqing, & Zhihao, 2020; Wang, Li, & Wu, 2022; Smales, 2022; Sohag, Gainetdinova, & Mariev, 2022).…”

Section: Historical Development and Literature Review Of Economic Unc...mentioning

confidence: 99%

The contagious effect of economic policy uncertainty in the post-crisis period

Şeker

2023

ECON

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PurposeThis study aims to analyze the contagious effects of economic policy uncertainties in the USA on the economies of its important trading partners, such as Japan, Canada, Mexico and the Eurozone.Design/methodology/approachIn the study using the uncertainty index created by Baker et al. (2016), the interaction between variables was analyzed with structural VAR (SVAR) models.FindingsAccording to the results obtained from the analysis, economic policy uncertainties in the USA had significant effects on the economies of its high-volume trading partners. The internal debt crisis experienced in the Eurozone after the 2008 crisis caused the European Central Bank to respond to the economic policy uncertainties in the USA with contractionary monetary policies, unlike other countries. In addition to these results, Mexico, which has a more fragile economic structure than other countries in the analysis, was more impacted by increasing uncertainties, as expected.Originality/valueThe present study aimed to bring a new perspective to the literature by evaluating the contagiousness of local uncertainty in the globalizing world and the monetary policies implemented as a precaution against this situation on an empirical plane.

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“…Referring to Lei et al (2018), the weight equation used in this article is

φ ((),, 1, w_{2}) goodbreak= \frac{{((), 1 goodbreak- k / K)}^{w_{2} - 1}}{\sum_{j = 1}^{K} {(1 - j / K)}^{w_{2} - 1}}

…”

Section: Volatility Model and Its Three Types Of Extended Modelsmentioning

confidence: 99%

“…On the contrary, if the p ‐value is less than 0.10, the MCS test will reject the extended model. The calculation method refers to the bootstrap process of Lei et al (2018), in which the control parameter d = 2 (block length) and the simulation times B = 10,000.…”

Section: Empirical Analysis and Robustnessmentioning

confidence: 99%

“…We have contributed to the following three aspects of the stock volatility forecasting model in financial markets compared to previous research. First, Lei et al (2018) show that the EPU index is time‐varying, which is relatively low with relatively small uncertainties. Therefore, this paper incorporates the SSE 50 Index and EPU Index into the GARCH‐MIDAS model, constructs the GARCH‐MIDAS‐RV‐EPU model, and compares and analyzes the effect of the EPU index of 22 different countries on the volatility prediction of the Chinese stock market.…”

Section: Introductionmentioning

confidence: 99%

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Volatility forecasting with an extended GARCH‐MIDAS approach

Li,

Ye,

Bhuiyan

et al. 2023

Journal of Forecasting

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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.

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Economic policy uncertainty and stock market activity: Evidence from China

Cited by 11 publications

References 34 publications

High-speed railway opening and urban green productivity in the post-COVID-19: Evidence from green finance

High-speed railway opening and urban green productivity in the post-COVID-19: Evidence from green finance

The contagious effect of economic policy uncertainty in the post-crisis period

Volatility forecasting with an extended GARCH‐MIDAS approach

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