IDEAS home Printed from https://ideas.repec.org/a/eee/econom/v239y2024i1s0304407623001665.html
   My bibliography  Save this article

Common volatility shocks driven by the global carbon transition

Author

Listed:
  • Campos-Martins, Susana
  • Hendry, David F.

Abstract

We propose a novel approach to measure the global effects of climate change news on financial markets. For that purpose, we first calculate the global common volatility of the oil and gas industry. Then we project it on climate-related shocks constructed using text-based proxies of climate change news. We show that rising concerns about the energy transition make oil and gas share prices move at the global scale, controlling for shocks to the oil price, US and world stock markets. Despite the clear exposure of oil and gas companies to carbon transition risk, not all geoclimatic shocks are alike. The signs and magnitudes of the impacts differ across climate risk drivers. Regarding sentiment, climate change news tends to create turmoil only when the news is negative. Moreover, the adverse effect is amplified by oil price movements but weakened by stock market shocks. Finally, our findings point out climate news materialises when it reaches the global scale, supporting the relevance of modelling geoclimatic volatility.

Suggested Citation

  • Campos-Martins, Susana & Hendry, David F., 2024. "Common volatility shocks driven by the global carbon transition," Journal of Econometrics, Elsevier, vol. 239(1).
    • Handle: RePEc:eee:econom:v:239:y:2024:i:1:s0304407623001665
    DOI: 10.1016/j.jeconom.2023.05.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304407623001665
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jeconom.2023.05.008?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    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," The Review of Financial Studies, Society for Financial Studies, vol. 33(3), pages 1184-1216.
    3. Simon Dietz & Alex Bowen & Charlie Dixon & Philip Gradwell, 2016. "‘Climate value at risk’ of global financial assets," Nature Climate Change, Nature, vol. 6(7), pages 676-679, July.
    4. Smales, L.A., 2021. "Geopolitical risk and volatility spillovers in oil and stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 358-366.
    5. David Ardia & Keven Bluteau & Kris Boudt & Koen Inghelbrecht, 2020. "Climate change concerns and the performance of green versus brown stocks," Working Paper Research 395, National Bank of Belgium.
    6. Kim, Tae-Hwan & White, Halbert, 2004. "On more robust estimation of skewness and kurtosis," Finance Research Letters, Elsevier, vol. 1(1), pages 56-73, March.
    7. 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.
    8. Frederick van der Ploeg & Armon Rezai, 2020. "Stranded Assets in the Transition to a Carbon-Free Economy," Annual Review of Resource Economics, Annual Reviews, vol. 12(1), pages 281-298, October.
    9. Herskovic, Bernard & Kelly, Bryan & Lustig, Hanno & Van Nieuwerburgh, Stijn, 2016. "The common factor in idiosyncratic volatility: Quantitative asset pricing implications," Journal of Financial Economics, Elsevier, vol. 119(2), pages 249-283.
    10. Stefano Battiston & Antoine Mandel & Irene Monasterolo & Franziska Schütze & Gabriele Visentin, 2017. "A climate stress-test of the financial system," Nature Climate Change, Nature, vol. 7(4), pages 283-288, April.
    11. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    12. Patrick Bolton & Marcin Kacperczyk, 2021. "Global Pricing of Carbon-Transition Risk," NBER Working Papers 28510, National Bureau of Economic Research, Inc.
    13. Engle, Robert F. & Campos-Martins, Susana, 2023. "What are the events that shake our world? Measuring and hedging global COVOL," Journal of Financial Economics, Elsevier, vol. 147(1), pages 221-242.
    14. Brandt, Michael W. & Gao, Lin, 2019. "Macro fundamentals or geopolitical events? A textual analysis of news events for crude oil," Journal of Empirical Finance, Elsevier, vol. 51(C), pages 64-94.
    15. Lutz Kilian & Daniel P. Murphy, 2014. "The Role Of Inventories And Speculative Trading In The Global Market For Crude Oil," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 454-478, April.
    16. Hong, Harrison & Li, Frank Weikai & Xu, Jiangmin, 2019. "Climate risks and market efficiency," Journal of Econometrics, Elsevier, vol. 208(1), pages 265-281.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Venturini, Alessio, 2022. "Climate change, risk factors and stock returns: A review of the literature," International Review of Financial Analysis, Elsevier, vol. 79(C).
    2. Zhu, Bo & Lin, Renda & Deng, Yuanyue & Chen, Pingshe & Chevallier, Julien, 2021. "Intersectoral systemic risk spillovers between energy and agriculture under the financial and COVID-19 crises," Economic Modelling, Elsevier, vol. 105(C).
    3. Zhao, Jing, 2022. "Exploring the influence of the main factors on the crude oil price volatility: An analysis based on GARCH-MIDAS model with Lasso approach," Resources Policy, Elsevier, vol. 79(C).
    4. Miriam Breitenstein & Duc Khuong Nguyen & Thomas Walther, 2021. "Environmental Hazards And Risk Management In The Financial Sector: A Systematic Literature Review," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 512-538, April.
    5. Cheng, Xian & Wu, Peng & Liao, Stephen Shaoyi & Wang, Xuelian, 2023. "An integrated model for crude oil forecasting: Causality assessment and technical efficiency," Energy Economics, Elsevier, vol. 117(C).
    6. Xing, Li-Min & Zhang, Yue-Jun, 2022. "Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?," Energy Economics, Elsevier, vol. 110(C).
    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. Liu, Yang & Han, Liyan & Xu, Yang, 2021. "The impact of geopolitical uncertainty on energy volatility," International Review of Financial Analysis, Elsevier, vol. 75(C).
    9. Cai, Yifei & Mignon, Valérie & Saadaoui, Jamel, 2022. "Not all political relation shocks are alike: Assessing the impacts of US–China tensions on the oil market," Energy Economics, Elsevier, vol. 114(C).
    10. Sevillano, María Caridad & Jareño, Francisco & López, Raquel & Esparcia, Carlos, 2024. "Connectedness between oil price shocks and US sector returns: Evidence from TVP-VAR and wavelet decomposition," Energy Economics, Elsevier, vol. 131(C).
    11. Bouri, Elie & Hammoud, Rami & Kassm, Christina Abou, 2023. "The effect of oil implied volatility and geopolitical risk on GCC stock sectors under various market conditions," Energy Economics, Elsevier, vol. 120(C).
    12. Nazlioglu, Saban & Gupta, Rangan & Gormus, Alper & Soytas, Ugur, 2020. "Price and volatility linkages between international REITs and oil markets," Energy Economics, Elsevier, vol. 88(C).
    13. Xiafei Li & Yu Wei & Xiaodan Chen & Feng Ma & Chao Liang & Wang Chen, 2022. "Which uncertainty is powerful to forecast crude oil market volatility? New evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4279-4297, October.
    14. Nguyen, Bao H. & Okimoto, Tatsuyoshi & Tran, Trung Duc, 2022. "Uncertainty-dependent and sign-dependent effects of oil market shocks," Journal of Commodity Markets, Elsevier, vol. 26(C).
    15. Tarek Bouazizi & Zouhaier Hadhek & Fatma Mrad & Mosbah Lafi, 2021. "Changes in Demand for Crude Oil and its Correlation with Crude Oil and Stock Market Returns Volatilities: Evidence from Three Asian Oil Importing Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 11(3), pages 27-43.
    16. Ferentinos, Konstantinos & Gibberd, Alex & Guin, Benjamin, 2023. "Stranded houses? The price effect of a minimum energy efficiency standard," Energy Economics, Elsevier, vol. 120(C).
    17. Wen, Xiaoqian & Xie, Yuxin & Pantelous, Athanasios A., 2022. "Extreme price co-movement of commodity futures and industrial production growth: An empirical evaluation," Energy Economics, Elsevier, vol. 108(C).
    18. Michael Barnett, 2024. "A Run on Fossil Fuel? Climate Change and Transition Risk," Papers 2410.00902, arXiv.org.
    19. Pástor, Ľuboš & Stambaugh, Robert F. & Taylor, Lucian A., 2022. "Dissecting green returns," Journal of Financial Economics, Elsevier, vol. 146(2), pages 403-424.
    20. Alessi, Lucia & Ossola, Elisa & Panzica, Roberto, 2019. "The Greenium matters: greenhouse gas emissions, environmental disclosures, and stock prices," Working Papers 2019-12, Joint Research Centre, European Commission, revised Apr 2020.

    More about this item

    Keywords

    Geoclimatic volatility shocks; Global common volatility; Multiplicative factor models; Climate transition risk; Oil and gas industry;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • 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
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:econom:v:239:y:2024:i:1:s0304407623001665. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jeconom .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.