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Energy-related uncertainty and Chinese stock market returns

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  • Wang, Yubao
  • Huang, Xiaozhou
  • Huang, Zhendong

Abstract

This study investigates the predictive power of energy-related uncertainty (EUI) from China, the U.S., and globally on Chinese stock market returns using the CSI 300 index as a representative and incorporating nine popular economic variables for comparison. The results show that the EUI is superior to predict Chinese stock returns, with China's EUI leading, followed by its global and U.S. counterparts. Additionally, the EUI outperforms nine popular economic variables. Cumulative squared forecast error confirms China's effectiveness in prediction. Robustness checks are consistent with the empirical results presented.

Suggested Citation

  • Wang, Yubao & Huang, Xiaozhou & Huang, Zhendong, 2024. "Energy-related uncertainty and Chinese stock market returns," Finance Research Letters, Elsevier, vol. 62(PB).
    • Handle: RePEc:eee:finlet:v:62:y:2024:i:pb:s1544612324002459
    DOI: 10.1016/j.frl.2024.105215
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    References listed on IDEAS

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    1. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    2. Dang, Tam Hoang-Nhat & Nguyen, Canh Phuc & Lee, Gabriel S. & Nguyen, Binh Quang & Le, Thuy Thu, 2023. "Measuring the energy-related uncertainty index," Energy Economics, Elsevier, vol. 124(C).
    3. Dashan Huang & Fuwei Jiang & Jun Tu & Guofu Zhou, 2015. "Investor Sentiment Aligned: A Powerful Predictor of Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 791-837.
    4. Husted, Lucas & Rogers, John & Sun, Bo, 2020. "Monetary policy uncertainty," Journal of Monetary Economics, Elsevier, vol. 115(C), pages 20-36.
    5. Kang, Wensheng & Ratti, Ronald A., 2013. "Oil shocks, policy uncertainty and stock market return," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 305-318.
    6. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    7. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    8. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    9. Steven Chu & Arun Majumdar, 2012. "Opportunities and challenges for a sustainable energy future," Nature, Nature, vol. 488(7411), pages 294-303, August.
    10. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    11. Li, Tao & Ma, Feng & Zhang, Xuehua & Zhang, Yaojie, 2020. "Economic policy uncertainty and the Chinese stock market volatility: Novel evidence," Economic Modelling, Elsevier, vol. 87(C), pages 24-33.
    12. Ma, Feng & Cao, Jiawei, 2023. "The Chinese equity premium predictability: Evidence from a long historical data," Finance Research Letters, Elsevier, vol. 53(C).
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