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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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    as
    1. Dario Caldara & Matteo Iacoviello, 2022. "Measuring Geopolitical Risk," American Economic Review, American Economic Association, vol. 112(4), pages 1194-1225, April.
    2. 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.
    3. Coleman, Les, 2012. "Explaining crude oil prices using fundamental measures," Energy Policy, Elsevier, vol. 40(C), pages 318-324.
    4. Robert F Engle & Stefano Giglio & Bryan Kelly & Heebum Lee & Johannes Stroebel, 2020. "Hedging Climate Change News," The Review of Financial Studies, Society for Financial Studies, vol. 33(3), pages 1184-1216.
    5. Hong, Harrison & Torous, Walter & Valkanov, Rossen, 2007. "Do industries lead stock markets?," Journal of Financial Economics, Elsevier, vol. 83(2), pages 367-396, February.
    6. Zhang, Yaojie & Ma, Feng & Wang, Yudong, 2019. "Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors?," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 97-117.
    7. Wang, Yudong & Hao, Xianfeng & Wu, Chongfeng, 2021. "Forecasting stock returns: A time-dependent weighted least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    8. Huang, Darien & Kilic, Mete, 2019. "Gold, platinum, and expected stock returns," Journal of Financial Economics, Elsevier, vol. 132(3), pages 50-75.
    9. Chen, Sichong, 2012. "The predictability of aggregate Japanese stock returns: Implications of dividend yield," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 284-304.
    10. 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.
    11. Robert B. Barsky & Lutz Kilian, 2004. "Oil and the Macroeconomy Since the 1970s," Journal of Economic Perspectives, American Economic Association, vol. 18(4), pages 115-134, Fall.
    12. Herrera, Ana María & Lagalo, Latika Gupta & Wada, Tatsuma, 2011. "Oil Price Shocks And Industrial Production: Is The Relationship Linear?," Macroeconomic Dynamics, Cambridge University Press, vol. 15(S3), pages 472-497, November.
    13. John H. Cochrane, 2011. "Presidential Address: Discount Rates," Journal of Finance, American Finance Association, vol. 66(4), pages 1047-1108, August.
    14. He, Mengxi & Zhang, Yaojie & Wen, Danyan & Wang, Yudong, 2021. "Forecasting crude oil prices: A scaled PCA approach," Energy Economics, Elsevier, vol. 97(C).
    15. Christophe McGlade & Paul Ekins, 2015. "The geographical distribution of fossil fuels unused when limiting global warming to 2 °C," Nature, Nature, vol. 517(7533), pages 187-190, January.
    16. Wang, Yudong & Pan, Zhiyuan & Wu, Chongfeng & Wu, Wenfeng, 2020. "Industry equi-correlation: A powerful predictor of stock returns," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 1-24.
    17. Ye, Liping, 2022. "The effect of climate news risk on uncertainties," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    18. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    19. Li, Jiahan & Tsiakas, Ilias, 2017. "Equity premium prediction: The role of economic and statistical constraints," Journal of Financial Markets, Elsevier, vol. 36(C), pages 56-75.
    20. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    21. Kyle C. Meng, 2017. "Using a Free Permit Rule to Forecast the Marginal Abatement Cost of Proposed Climate Policy," American Economic Review, American Economic Association, vol. 107(3), pages 748-784, March.
    22. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Tran, Vuong Thao, 2018. "Can economic policy uncertainty predict stock returns? Global evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 134-150.
    23. 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.
    24. 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.
    25. Stephie Fried & Kevin Novan & William B. Peterman, 2021. "The Macro Effects of Climate Policy Uncertainty," Finance and Economics Discussion Series 2021-018, Board of Governors of the Federal Reserve System (U.S.).
    26. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    27. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    28. Chang, Bo Young & Christoffersen, Peter & Jacobs, Kris, 2013. "Market skewness risk and the cross section of stock returns," Journal of Financial Economics, Elsevier, vol. 107(1), pages 46-68.
    29. Bianconi, Marcelo & Esposito, Federico & Sammon, Marco, 2021. "Trade policy uncertainty and stock returns," Journal of International Money and Finance, Elsevier, vol. 119(C).
    30. Londono, Juan M. & Zhou, Hao, 2017. "Variance risk premiums and the forward premium puzzle," Journal of Financial Economics, Elsevier, vol. 124(2), pages 415-440.
    31. Li, Jun & Yu, Jianfeng, 2012. "Investor attention, psychological anchors, and stock return predictability," Journal of Financial Economics, Elsevier, vol. 104(2), pages 401-419.
    32. Chen, Hongyi & Tillmann, Peter, 2021. "Monetary policy uncertainty in China," Journal of International Money and Finance, Elsevier, vol. 110(C).
    33. John H. Cochrane, 2008. "The Dog That Did Not Bark: A Defense of Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1533-1575, July.
    34. Manela, Asaf & Moreira, Alan, 2017. "News implied volatility and disaster concerns," Journal of Financial Economics, Elsevier, vol. 123(1), pages 137-162.
    35. Diaz-Rainey, Ivan & Gehricke, Sebastian A. & Roberts, Helen & Zhang, Renzhu, 2021. "Trump vs. Paris: The impact of climate policy on U.S. listed oil and gas firm returns and volatility," International Review of Financial Analysis, Elsevier, vol. 76(C).
    36. Byeong-Je An & Andrew Ang & Turan G. Bali & Nusret Cakici, 2014. "The Joint Cross Section of Stocks and Options," Journal of Finance, American Finance Association, vol. 69(5), pages 2279-2337, October.
    37. Stambaugh, Robert F., 1999. "Predictive regressions," Journal of Financial Economics, Elsevier, vol. 54(3), pages 375-421, December.
    38. Jonathan Brogaard & Andrew Detzel, 2015. "The Asset-Pricing Implications of Government Economic Policy Uncertainty," Management Science, INFORMS, vol. 61(1), pages 3-18, January.
    39. Roger D. Huang & Ronald W. Masulis & Hans R. Stoll, 1996. "Energy shocks and financial markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 16(1), pages 1-27, February.
    40. Sarwar, Ghulam, 2014. "U.S. stock market uncertainty and cross-market European stock returns," Journal of Multinational Financial Management, Elsevier, vol. 28(C), pages 1-14.
    41. Jian Chen & Fuwei Jiang & Guoshi Tong, 2017. "Economic policy uncertainty in China and stock market expected returns," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 57(5), pages 1265-1286, December.
    42. Hartley, Peter & Medlock III, Kenneth B., 2008. "A model of the operation and development of a National Oil Company," Energy Economics, Elsevier, vol. 30(5), pages 2459-2485, September.
    43. Miao, Hong & Ramchander, Sanjay & Wang, Tianyang & Yang, Dongxiao, 2017. "Influential factors in crude oil price forecasting," Energy Economics, Elsevier, vol. 68(C), pages 77-88.
    44. Peng, Lin & Xiong, Wei, 2006. "Investor attention, overconfidence and category learning," Journal of Financial Economics, Elsevier, vol. 80(3), pages 563-602, June.
    45. Stefano Giglio & Matteo Maggiori & Krishna Rao & Johannes Stroebel & Andreas Weber & Stijn Van Nieuwerburgh, 2021. "Climate Change and Long-Run Discount Rates: Evidence from Real Estate [Abrupt climate change]," The Review of Financial Studies, Society for Financial Studies, vol. 34(8), pages 3527-3571.
    46. Jiang, Fuwei & Lee, Joshua & Martin, Xiumin & Zhou, Guofu, 2019. "Manager sentiment and stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 126-149.
    47. 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.
    48. Thai-Ha Le, Youngho Chang, and Donghyun Park, 2020. "Renewable and Nonrenewable Energy Consumption, Economic Growth, and Emissions: International Evidence," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 73-92.
    49. Driesprong, Gerben & Jacobsen, Ben & Maat, Benjamin, 2008. "Striking oil: Another puzzle?," Journal of Financial Economics, Elsevier, vol. 89(2), pages 307-327, August.
    50. Rapach, David E. & Ringgenberg, Matthew C. & Zhou, Guofu, 2016. "Short interest and aggregate stock returns," Journal of Financial Economics, Elsevier, vol. 121(1), pages 46-65.
    51. Fama, Eugene F. & French, Kenneth R., 1989. "Business conditions and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 25(1), pages 23-49, November.
    52. Azi Ben-Rephael & Zhi Da & Ryan D. Israelsen, 2017. "It Depends on Where You Search: Institutional Investor Attention and Underreaction to News," The Review of Financial Studies, Society for Financial Studies, vol. 30(9), pages 3009-3047.
    53. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2006. "The Cross‐Section of Volatility and Expected Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 259-299, February.
    54. Rapach, David E. & Ringgenberg, Matthew C. & Zhou, Guofu, 2016. "Short interest and aggregate stock returns," Journal of Financial Economics, Elsevier, vol. 121(1), pages 46-65.
    55. Thomas C. Chiang, 2021. "Geopolitical risk, economic policy uncertainty and asset returns in Chinese financial markets," China Finance Review International, Emerald Group Publishing Limited, vol. 11(4), pages 474-501, March.
    56. 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).
    57. Mork, Knut Anton, 1989. "Oil and Macroeconomy When Prices Go Up and Down: An Extension of Hamilton's Results," Journal of Political Economy, University of Chicago Press, vol. 97(3), pages 740-744, June.
    58. Huang, Dashan & Li, Jiangyuan & Wang, Liyao, 2021. "Are disagreements agreeable? Evidence from information aggregation," Journal of Financial Economics, Elsevier, vol. 141(1), pages 83-101.
    59. Wang, Yudong & Wei, Yu & Wu, Chongfeng & Yin, Libo, 2018. "Oil and the short-term predictability of stock return volatility," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 90-104.
    60. Schlenker, Wolfram & Taylor, Charles A., 2021. "Market expectations of a warming climate," Journal of Financial Economics, Elsevier, vol. 142(2), pages 627-640.
    61. Peter Erickson & Michael Lazarus & Georgia Piggot, 2018. "Limiting fossil fuel production as the next big step in climate policy," Nature Climate Change, Nature, vol. 8(12), pages 1037-1043, December.
    62. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," The Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
    63. Zaremba, Adam & Cakici, Nusret & Demir, Ender & Long, Huaigang, 2022. "When bad news is good news: Geopolitical risk and the cross-section of emerging market stock returns," Journal of Financial Stability, Elsevier, vol. 58(C).
    64. Devpura, Neluka & Narayan, Paresh Kumar & Sharma, Susan Sunila, 2021. "Bond return predictability: Evidence from 25 OECD countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    65. Wang, Yudong & Pan, Zhiyuan & Liu, Li & Wu, Chongfeng, 2019. "Oil price increases and the predictability of equity premium," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 43-58.
    66. Dong Lou, 2014. "Attracting Investor Attention through Advertising," The Review of Financial Studies, Society for Financial Studies, vol. 27(6), pages 1797-1829.
    67. Gupta, Kartick & Krishnamurti, Chandrasekhar, 2018. "Do macroeconomic conditions and oil prices influence corporate risk-taking?," Journal of Corporate Finance, Elsevier, vol. 53(C), pages 65-86.
    68. Kurov, Alexander & Stan, Raluca, 2018. "Monetary policy uncertainty and the market reaction to macroeconomic news," Journal of Banking & Finance, Elsevier, vol. 86(C), pages 127-142.
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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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