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The differential effects of climate risks on non-fossil and fossil fuel stock markets: Evidence from China

Author

Listed:
  • Zhu, Bo
  • Hu, Xin
  • Deng, Yuanyue
  • Zhang, Bokai
  • Li, Xiru

Abstract

This paper estimates the effects of climate risks on the stock returns in China, differentiating between non-fossil and fossil fuel firms, using a time-varying parametric vector autoregressive (TVP-VAR) model. The news-based climate physical risk (CPR) and climate transition risk (CTR) indexes for China are constructed. The results show that both types of climate risks have time-varying and differential effects on the returns of non-fossil and fossil fuel stocks. The differential effects are associated with investor preference and cash-flow effects. Besides, CTR contributes more connectedness to the return premium between the two stock types than CPR.

Suggested Citation

  • Zhu, Bo & Hu, Xin & Deng, Yuanyue & Zhang, Bokai & Li, Xiru, 2023. "The differential effects of climate risks on non-fossil and fossil fuel stock markets: Evidence from China," Finance Research Letters, Elsevier, vol. 55(PB).
    • Handle: RePEc:eee:finlet:v:55:y:2023:i:pb:s1544612323003343
    DOI: 10.1016/j.frl.2023.103962
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    as
    1. Dario Caldara & Matteo Iacoviello, 2022. "Measuring Geopolitical Risk," American Economic Review, American Economic Association, vol. 112(4), pages 1194-1225, April.
    2. 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.
    3. Bua, Giovanna & Kapp, Daniel & Ramella, Federico & Rognone, Lavinia, 2022. "Transition versus physical climate risk pricing in European financial markets: a text-based approach," Working Paper Series 2677, European Central Bank.
    4. Huang, Darien & Kilic, Mete, 2019. "Gold, platinum, and expected stock returns," Journal of Financial Economics, Elsevier, vol. 132(3), pages 50-75.
    5. Saunders, Edward M, Jr, 1993. "Stock Prices and Wall Street Weather," American Economic Review, American Economic Association, vol. 83(5), pages 1337-1345, December.
    6. Zouhaier Dhifaoui & Rabeh Khalfaoui & Sami Ben Jabeur & Mohammad Zoynul Abedin, 2023. "Exploring the effect of climate risk on agricultural and food stock prices: Fresh evidence from EMD-Based variable-lag transfer entropy analysis," Post-Print hal-03998224, HAL.
    7. 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).
    8. Treepongkaruna, Sirimon & Chan, Kam Fong & Malik, Ihtisham, 2023. "Climate policy uncertainty and the cross-section of stock returns," Finance Research Letters, Elsevier, vol. 55(PA).
    9. Tian, Hao & Long, Shaobo & Li, Zixuan, 2022. "Asymmetric effects of climate policy uncertainty, infectious diseases-related uncertainty, crude oil volatility, and geopolitical risks on green bond prices," Finance Research Letters, Elsevier, vol. 48(C).
    10. 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.
    11. Yan, Wan-Lin & Cheung, Adrian (Wai Kong), 2023. "The dynamic spillover effects of climate policy uncertainty and coal price on carbon price: Evidence from China," Finance Research Letters, Elsevier, vol. 53(C).
    12. Chang, Shao-Chi & Chen, Sheng-Syan & Chou, Robin K. & Lin, Yueh-Hsiang, 2008. "Weather and intraday patterns in stock returns and trading activity," Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1754-1766, September.
    13. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    14. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    15. Liu, Peizhi & Qiao, Haishu, 2021. "How does China's decarbonization policy influence the value of carbon-intensive firms?," Finance Research Letters, Elsevier, vol. 43(C).
    16. Nakajima, Jouchi & Kasuya, Munehisa & Watanabe, Toshiaki, 2011. "Bayesian analysis of time-varying parameter vector autoregressive model for the Japanese economy and monetary policy," Journal of the Japanese and International Economies, Elsevier, vol. 25(3), pages 225-245, September.
    17. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    18. Zeng, Qing & Ma, Feng & Lu, Xinjie & Xu, Weiju, 2022. "Policy uncertainty and carbon neutrality: Evidence from China," Finance Research Letters, Elsevier, vol. 47(PB).
    19. Jin, Yi & Zhao, Hang & Bu, Lin & Zhang, Dayong, 2023. "Geopolitical risk, climate risk and energy markets: A dynamic spillover analysis," International Review of Financial Analysis, Elsevier, vol. 87(C).
    20. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2020. "Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions," JRFM, MDPI, vol. 13(4), pages 1-23, April.
    21. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
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    Cited by:

    1. Wang Gao & Jiajia Wei & Shixiong Yang, 2023. "The Asymmetric Effects of Extreme Climate Risk Perception on Coal Futures Return Dynamics: Evidence from Nonparametric Causality-In-Quantiles Tests," Sustainability, MDPI, vol. 15(10), pages 1-19, May.
    2. Xin Zhang & Mateng Zhang & Zhong Fang, 2023. "Impact of Climate Risk on the Financial Performance and Financial Policies of Enterprises," Sustainability, MDPI, vol. 15(20), pages 1-24, October.

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    More about this item

    Keywords

    Climate physical risk; Climate transition risk; Non-fossil fuel stocks; Fossil fuel stocks; Varying parametric vector autoregressive model;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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