Common volatility shocks driven by the global carbon transition

Susana Campos-Martins; David F. Hendry

doi:10.1016/j.jeconom.2023.05.008

Common volatility shocks driven by the global carbon transition

Susana Campos-Martins^*, David F. Hendry^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

16 Citations (Scopus)

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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.

Original language	English
Article number	105472
Journal	Journal of Econometrics
Volume	239
Issue number	1
DOIs	https://doi.org/10.1016/j.jeconom.2023.05.008
Publication status	Published - Feb 2024

Keywords

Geoclimatic volatility shocks
Global common volatility
Multiplicative factor models
Climate transition risk
Oil and gas industry

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Cite this

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title = "Common volatility shocks driven by the global carbon transition",

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.",

keywords = "Geoclimatic volatility shocks, Global common volatility, Multiplicative factor models, Climate transition risk, Oil and gas industry",

author = "Susana Campos-Martins and Hendry, {David F.}",

note = "Funding Information: Thanks to the referees and especially Serena Ng for their helpful suggestions. We also thank Robert F. Engle and the participants in the International Conference on Computational and Financial Econometrics in December 2019, the 2020 European Geosciences Union Virtual Session on Economics and Econometrics of Climate Change in May 2020, the 2020 World Congress of the Econometric Society Session on Climate Change Modelling in August 2020, the Climate Exp0 - COP26 Universities Network Virtual Conference in May 2021, the 5th (virtual) Conference on Econometric Models of Climate Change in August 2021, the 20th International Conference on Credit Risk Evaluation in September 2021, the Heriot-Watt University and University of St Andrews COP26 Fringe Event at Panmure House in November 2021, the EC Virtual Conference on Econometrics of Climate, Energy, and Resources in December 2021, the 14th Annual SoFiE Conference in June 2022, and the seminars at University of Rome Tor Vergata, University of Minho, Bank of Italy, University College London and University of Oxford. Part of this work was developed while the first author was visiting the Department of Statistical Sciences of the University of Padova in Padua, Italy. The first author thanks Massimiliano Caporin for his kind hospitality and the very helpful comments and guidance in the initial phase of the investigation. The financial support provided through the Young Investigator Training Program research prize by the ACRI Foundation, Italy and IV Econometric Models of Climate Change Conference at the University of Milan-Bicocca on August 29–30, 2019, and from the Robertson Foundation, United States (award 9907422 ) is gratefully acknowledged. Funding Information: Thanks to the referees and especially Serena Ng for their helpful suggestions. We also thank Robert F. Engle and the participants in the International Conference on Computational and Financial Econometrics in December 2019, the 2020 European Geosciences Union Virtual Session on Economics and Econometrics of Climate Change in May 2020, the 2020 World Congress of the Econometric Society Session on Climate Change Modelling in August 2020, the Climate Exp0 - COP26 Universities Network Virtual Conference in May 2021, the 5th (virtual) Conference on Econometric Models of Climate Change in August 2021, the 20th International Conference on Credit Risk Evaluation in September 2021, the Heriot-Watt University and University of St Andrews COP26 Fringe Event at Panmure House in November 2021, the EC2 Virtual Conference on Econometrics of Climate, Energy, and Resources in December 2021, the 14th Annual SoFiE Conference in June 2022, and the seminars at University of Rome Tor Vergata, University of Minho, Bank of Italy, University College London and University of Oxford. Part of this work was developed while the first author was visiting the Department of Statistical Sciences of the University of Padova in Padua, Italy. The first author thanks Massimiliano Caporin for his kind hospitality and the very helpful comments and guidance in the initial phase of the investigation. The financial support provided through the Young Investigator Training Program research prize by the ACRI Foundation, Italy and IV Econometric Models of Climate Change Conference at the University of Milan-Bicocca on August 29–30, 2019, and from the Robertson Foundation, United States (award 9907422) is gratefully acknowledged. Publisher Copyright: {\textcopyright} 2023 The Author(s)",

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N2 - 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.

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Common volatility shocks driven by the global carbon transition

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CUBE: Católica Lisbon Research Unit in Business and Economics

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Common volatility shocks driven by the global carbon transition

Abstract

Keywords

UN SDGs

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CUBE: Católica Lisbon Research Unit in Business and Economics

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