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Climate policy uncertainty and the stock return predictability of the oil industry

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  • He, Mengxi
  • Zhang, Yaojie

Abstract

This paper uses a news-based climate policy uncertainty (CPU) proposed by Gavriilidis (2021) to test the stock return predictability of the oil industry. Results show that CPU is a strong predictor of future oil industry stock returns both in- and out-of-sample. The predictive power of CPU is informationally complementary to existing uncertainty indicators and far greater than that of other uncertainty indicators, economic variables, new predictors, and oil industry-specific predictors. Furthermore, CPU can provide sizeable economic gains to mean–variance investors. The driving force of CPU’s predictive power appears to stem from its ability to predict future cash flows in the oil industry. We also explain the predictability of CPU from the perspective of oil-related fundamentals and investor attention.

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  • He, Mengxi & Zhang, Yaojie, 2022. "Climate policy uncertainty and the stock return predictability of the oil industry," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    • Handle: RePEc:eee:intfin:v:81:y:2022:i:c:s1042443122001470
    DOI: 10.1016/j.intfin.2022.101675
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    Cited by:

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    3. Zhang, Yaojie & He, Mengxi & Liao, Cunfei & Wang, Yudong, 2023. "Climate risk exposure and the cross-section of Chinese stock returns," Finance Research Letters, Elsevier, vol. 55(PB).
    4. Xu, Yongan & Duong, Duy & Xu, Hualong, 2023. "Attention! Predicting crude oil prices from the perspective of extreme weather," Finance Research Letters, Elsevier, vol. 57(C).
    5. Hyeon-Seok Kim & Hui-Sang Kim & Sun-Yong Choi, 2024. "Investigating the Impact of Agricultural, Financial, Economic, and Political Factors on Oil Forward Prices and Volatility: A SHAP Analysis," Energies, MDPI, vol. 17(5), pages 1-24, February.
    6. Mengxi He & Yudong Wang & Yaojie Zhang, 2023. "The predictability of iron ore futures prices: A product‐material lead–lag effect," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(9), pages 1289-1304, September.
    7. Xu, Yongan & Li, Ming & Yan, Wen & Bai, Jiancheng, 2022. "Predictability of the renewable energy market returns: The informational gains from the climate policy uncertainty," Resources Policy, Elsevier, vol. 79(C).
    8. He, Mengxi & Wang, Yudong & Zeng, Qing & Zhang, Yaojie, 2023. "Forecasting aggregate stock market volatility with industry volatilities: The role of spillover index," Research in International Business and Finance, Elsevier, vol. 65(C).
    9. Guesmi, Khaled & Makrychoriti, Panagiota & Spyrou, Spyros, 2023. "The relationship between climate risk, climate policy uncertainty, and CO2 emissions: Empirical evidence from the US," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 610-628.
    10. Huthaifa Sameeh Alqaralleh, 2023. "The extreme spillover from climate policy uncertainty to the Chinese sector stock market: wavelet time-varying approach," Letters in Spatial and Resource Sciences, Springer, vol. 16(1), pages 1-17, December.

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    More about this item

    Keywords

    Climate policy uncertainty; Return predictability; Oil industry; Cash flow; Investor attention;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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