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Global economic policy uncertainty and stock volatility: evidence from emerging economies

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  • Xiaoling Yu
  • Yirong Huang
  • Kaitian Xiao

Abstract

We investigate the impact of the global economic policy uncertainty (GEPU) on stock volatility for nine emerging economies (Brazil, Russia, India, China, South Africa, Mexico, Indonesia, South Korea, and Turkey). We employ an expanded GARCH-MIDAS approach to connect low-frequency GEPU data and high-frequency stock data, assuming that GEPU affects stock volatility via the long-run component of total volatility. We not only use DM and SPA tests to statically evaluate the out-of-sample forecasting ability of the extended model, taking traditional GARCH model and GARCH-MIDAS model as benchmarks, but also use the Fluctuation test to examine the time-varyingly relative forecasting performance in the presence of potential instability. From the in-sample estimation results, we find that GEPU has empirically significant impact on stock volatility for the nine emerging economies. The out-of-sample forecasting results show that the GEPU-based model can improve forecasting performance of stock volatility for emerging markets, especially in unstable environments.

Suggested Citation

  • Xiaoling Yu & Yirong Huang & Kaitian Xiao, 2021. "Global economic policy uncertainty and stock volatility: evidence from emerging economies," Journal of Applied Economics, Taylor & Francis Journals, vol. 24(1), pages 416-440, January.
  • Handle: RePEc:taf:recsxx:v:24:y:2021:i:1:p:416-440
    DOI: 10.1080/15140326.2021.1953913
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    Cited by:

    1. Marobhe, Mutaju Isaack & Kansheba, Jonathan Mukiza, 2024. "Airlines and climate policy uncertainty: Are the sector's stocks soaring or stalling?," Journal of Air Transport Management, Elsevier, vol. 115(C).
    2. Li, Rong & Tang, Guangyuan & Hong, Chen & Li, Sufang & Li, Bingting & Xiang, Shujian, 2024. "A study on economic policy uncertainty, geopolitical risk and stock market spillovers in BRICS countries," The North American Journal of Economics and Finance, Elsevier, vol. 73(C).
    3. Liu, Tao & Guan, Xinyue & Wei, Yigang & Xue, Shan & Xu, Liang, 2023. "Impact of economic policy uncertainty on the volatility of China's emission trading scheme pilots," Energy Economics, Elsevier, vol. 121(C).
    4. Chang, Kuang-Liang, 2022. "Do economic policy uncertainty indices matter in joint volatility cycles between U.S. and Japanese stock markets?," Finance Research Letters, Elsevier, vol. 47(PA).
    5. D’Amato, Valeria & Levantesi, Susanna & Piscopo, Gabriella, 2022. "Deep learning in predicting cryptocurrency volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    6. Eiji Ogawa & Pengfei Luo, 2024. "Macroeconomic effects of global policy and financial risks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 177-205, January.
    7. Chen, Peng & Miao, Xinru & Tee, Kai-Hong, 2023. "Do gold prices respond more to uncertainty shocks at the zero lower bound?," Resources Policy, Elsevier, vol. 86(PA).
    8. Han Liu & Peng Yang & Haiyan Song & Doris Chenguang Wu, 2024. "Global and domestic economic policy uncertainties and tourism stock market: Evidence from China," Tourism Economics, , vol. 30(3), pages 567-591, May.
    9. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Gupta, Rangan & Bouri, Elie, 2024. "Energy-related uncertainty and international stock market volatility," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 280-293.
    10. Guo, Kun & Liu, Fengqi & Sun, Xiaolei & Zhang, Dayong & Ji, Qiang, 2023. "Predicting natural gas futures’ volatility using climate risks," Finance Research Letters, Elsevier, vol. 55(PA).

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