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Climate risk and Chinese stock volatility forecasting: Evidence from ESG index

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  • Wang, Jiqian
  • Li, Liang

Abstract

This study employs a generalised autoregressive conditional heteroscedasticity mixed data sampling model (GARCH-MIDAS) to explore the forecasting performance of Chinese climate uncertainty (CU), Chinese climate policy uncertainty (CEU), Chinese economic policy uncertainty (CEPU), and US climate policy uncertainty (UCU) in both CSI 300 ESG and SSEC index volatility forecasting. The empirical results indicate that CU and CEU can significantly drive CSI 300 ESG volatility and outperform CEU and UCU. This may be caused by investors paying more attention to climate risk with the advent of the ESG score.

Suggested Citation

  • Wang, Jiqian & Li, Liang, 2023. "Climate risk and Chinese stock volatility forecasting: Evidence from ESG index," Finance Research Letters, Elsevier, vol. 55(PA).
  • Handle: RePEc:eee:finlet:v:55:y:2023:i:pa:s1544612323002702
    DOI: 10.1016/j.frl.2023.103898
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    1. Robert F Engle & Stefano Giglio & Bryan Kelly & Heebum Lee & Johannes Stroebel, 2020. "Hedging Climate Change News," Review of Financial Studies, Society for Financial Studies, vol. 33(3), pages 1184-1216.
    2. Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
    3. Ströbel, Johannes & Wurgler, Jeffrey, 2021. "What do you think about climate finance?," CEPR Discussion Papers 16622, C.E.P.R. Discussion Papers.
    4. Tim Bollerslev & Benjamin Hood & John Huss & Lasse Heje Pedersen, 2018. "Risk Everywhere: Modeling and Managing Volatility," Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2729-2773.
    5. Chenet, Hugues & Ryan-Collins, Josh & van Lerven, Frank, 2021. "Finance, climate-change and radical uncertainty: Towards a precautionary approach to financial policy," Ecological Economics, Elsevier, vol. 183(C).
    6. Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2023. "Climate risks and realized volatility of major commodity currency exchange rates," Journal of Financial Markets, Elsevier, vol. 62(C).
    7. Pan, Zhiyuan & Wang, Yudong & Wu, Chongfeng & Yin, Libo, 2017. "Oil price volatility and macroeconomic fundamentals: A regime switching GARCH-MIDAS model," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 130-142.
    8. Emanuele Campiglio & Yannis Dafermos & Pierre Monnin & Josh Ryan-Collins & Guido Schotten & Misa Tanaka, 2018. "Climate change challenges for central banks and financial regulators," Nature Climate Change, Nature, vol. 8(6), pages 462-468, June.
    9. Khalfaoui, Rabeh & Mefteh-Wali, Salma & Viviani, Jean-Laurent & Ben Jabeur, Sami & Abedin, Mohammad Zoynul & Lucey, Brian M., 2022. "How do climate risk and clean energy spillovers, and uncertainty affect U.S. stock markets?," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    10. Lv, Wendai & Li, Bin, 2023. "Climate policy uncertainty and stock market volatility: Evidence from different sectors," Finance Research Letters, Elsevier, vol. 51(C).
    11. I. El Ouadghiri & K. Guesmi & Jonathan Peillex & A. Ziegler, 2021. "Public Attention to Environmental Issues and Stock Market Returns," Post-Print hal-03678291, HAL.
    12. 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.
    13. El Ouadghiri, Imane & Guesmi, Khaled & Peillex, Jonathan & Ziegler, Andreas, 2021. "Public Attention to Environmental Issues and Stock Market Returns," Ecological Economics, Elsevier, vol. 180(C).
    14. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    15. Dang, Dandan & Fang, Hongsheng & He, Minyuan, 2019. "Economic policy uncertainty, tax quotas and corporate tax burden: Evidence from China," China Economic Review, Elsevier, vol. 56(C), pages 1-1.
    16. Ma, Feng & Lu, Xinjie & Liu, Jia & Huang, Dengshi, 2022. "Macroeconomic attention and stock market return predictability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    17. Wang, Lu & Ma, Feng & Liu, Jing & Yang, Lin, 2020. "Forecasting stock price volatility: New evidence from the GARCH-MIDAS model," International Journal of Forecasting, Elsevier, vol. 36(2), pages 684-694.
    18. Liang, Chao & Umar, Muhammad & Ma, Feng & Huynh, Toan L.D., 2022. "Climate policy uncertainty and world renewable energy index volatility forecasting," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    19. Feng Ma & Xinjie Lu & Lu Wang & Julien Chevallier, 2021. "Global economic policy uncertainty and gold futures market volatility: Evidence from Markov regime‐switching GARCH‐MIDAS models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1070-1085, September.
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