IDEAS home Printed from https://ideas.repec.org/p/fem/femwpa/2024.22.html
   My bibliography  Save this paper

Causality, Connectedness, and Volatility Pass-through among Energy-Metal-Stock-Carbon Markets: New Evidence from the EU

Author

Listed:
  • Parisa Pakrooh

    (Marie Sklodowska-Curie Postdoctoral Research Fellow, Fondazione Eni Enrico Mattei)

  • Matteo Manera

    (Department of Economics, Management and Statistics, University of Milano-Bicocca, and Fondazione Eni Enrico Mattei)

Abstract

The EU carbon market serves as an innovative financial instrument with the primary objective of contributing to mitigate the impacts of climate change. This market demonstrates significant interconnectedness with fossil energy, precious metal, and financial markets, although limited research has focused on the causality, dependency, intensity and direction of time-varying spillover effects. This study aims to investigate the causality direction, degree of dependency structure, and volatility transmission from Brent Oil, UK Natural Gas, Rotterdam Coal, Gold, Silver, Copper, and EuroStoxx600 future prices to EU Allowances during different periods of EU market. To achieve these objectives, this paper proposes a novel methodological approach that combines the most recent econometrics methods, such as Directed Acyclic Graph analysis, C-Vine Copula models, and Time-Varying parameter Vector Auto Regressive models with Stochastic Volatility with the use of a comprehensive sample of daily data from 26 April 2005 to 31 December 2022. The major findings of this study demonstrate that causality predominantly runs from energy, metal, and financial markets to the EU carbon market. The dependency structure, although varying across different sub-periods, shows a strong relationship observed between oil, coal, silver, copper, EuroStoxx600, and CO2 market. Additionally, the oil and copper futures prices exhibit the highest dependence on EUA prices. Furthermore, the study establishes that the EU carbon market is a net receiver of shocks from all other markets, with the energy, metal, and financial markets significantly influencing volatility in EUA prices. The time-varying spillover effect is most pronounced with a one-day lag, and the duration of the spillover effects ranges from 2 to 15 days, gradually diminishing over time. These results have the potential to increase the understanding of the EU carbon market and offer practical guidance for policymakers, investors, and companies involved in this domain.

Suggested Citation

  • Parisa Pakrooh & Matteo Manera, 2024. "Causality, Connectedness, and Volatility Pass-through among Energy-Metal-Stock-Carbon Markets: New Evidence from the EU," Working Papers 2024.22, Fondazione Eni Enrico Mattei.
  • Handle: RePEc:fem:femwpa:2024.22
    as

    Download full text from publisher

    File URL: https://feem-media.s3.eu-central-1.amazonaws.com/wp-content/uploads/2-NDL2024-22-1.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Quanrui Song & Jianxu Liu & Songsak Sriboonchitta, 2019. "Risk Measurement of Stock Markets in BRICS, G7, and G20: Vine Copulas versus Factor Copulas," Mathematics, MDPI, vol. 7(3), pages 1-16, March.
    2. Nelson, Charles R & Piger, Jeremy & Zivot, Eric, 2001. "Markov Regime Switching and Unit-Root Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(4), pages 404-415, October.
    3. Zhu, Bangzhu & Ye, Shunxin & Han, Dong & Wang, Ping & He, Kaijian & Wei, Yi-Ming & Xie, Rui, 2019. "A multiscale analysis for carbon price drivers," Energy Economics, Elsevier, vol. 78(C), pages 202-216.
    4. Chevallier, Julien & Khuong Nguyen, Duc & Carlos Reboredo, Juan, 2019. "A conditional dependence approach to CO2-energy price relationships," Energy Economics, Elsevier, vol. 81(C), pages 812-821.
    5. Aslan, Aydin & Posch, Peter N., 2022. "Does carbon price volatility affect European stock market sectors? A connectedness network analysis," Finance Research Letters, Elsevier, vol. 50(C).
    6. Fazal, Rizwan & Bhatti, M. Ishaq & Rehman, Atiq Ur, 2022. "Causality Analysis: The study of Size and Power based on riz-PC Algorithm of Graph Theoretic Approach," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    7. Zhang, Qi & Di, Peng & Farnoosh, Arash, 2021. "Study on the impacts of Shanghai crude oil futures on global oil market and oil industry based on VECM and DAG models," Energy, Elsevier, vol. 223(C).
    8. Creti, Anna & Jouvet, Pierre-André & Mignon, Valérie, 2012. "Carbon price drivers: Phase I versus Phase II equilibrium?," Energy Economics, Elsevier, vol. 34(1), pages 327-334.
    9. Selva Demiralp & Kevin D. Hoover, 2003. "Searching for the Causal Structure of a Vector Autoregression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 745-767, December.
    10. repec:dau:papers:123456789/5269 is not listed on IDEAS
    11. 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.
    12. Reboredo, Juan C., 2013. "Modeling EU allowances and oil market interdependence. Implications for portfolio management," Energy Economics, Elsevier, vol. 36(C), pages 471-480.
    13. Izzeldin, Marwan & Muradoğlu, Yaz Gülnur & Pappas, Vasileios & Petropoulou, Athina & Sivaprasad, Sheeja, 2023. "The impact of the Russian-Ukrainian war on global financial markets," International Review of Financial Analysis, Elsevier, vol. 87(C).
    14. Hammoudeh, Shawkat & Nguyen, Duc Khuong & Sousa, Ricardo M., 2014. "What explain the short-term dynamics of the prices of CO2 emissions?," Energy Economics, Elsevier, vol. 46(C), pages 122-135.
    15. He, Zhifang, 2023. "Geopolitical risks and investor sentiment: Causality and TVP-VAR analysis," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    16. Qi Zhang & Peng Di & Arash Farnoosh, 2021. "Study on the impacts of Shanghai crude oil futures on global oil market and oil industry based on VECM and DAG models," Post-Print hal-03151102, HAL.
    17. Reboredo, Juan C., 2014. "Volatility spillovers between the oil market and the European Union carbon emission market," Economic Modelling, Elsevier, vol. 36(C), pages 229-234.
    18. Kim, Jong-Min & Kim, Dong H. & Jung, Hojin, 2021. "Estimating yield spreads volatility using GARCH-type models," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    19. Guo, Yaoqi & Shi, Fengyuan & Lin, Boqiang & Zhang, Hongwei, 2023. "The impact of oil shocks from different sources on China's clean energy metal stocks: An analysis of spillover effects based on a time-varying perspective," Resources Policy, Elsevier, vol. 81(C).
    20. Frank Venmans, 2015. "Capital market response to emission allowance prices: a multivariate GARCH approach," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 17(4), pages 577-620, October.
    21. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 29, pages 107-142, November.
    22. Gong, Xu & Shi, Rong & Xu, Jun & Lin, Boqiang, 2021. "Analyzing spillover effects between carbon and fossil energy markets from a time-varying perspective," Applied Energy, Elsevier, vol. 285(C).
    23. Tan, Xue-Ping & Wang, Xin-Yu, 2017. "Dependence changes between the carbon price and its fundamentals: A quantile regression approach," Applied Energy, Elsevier, vol. 190(C), pages 306-325.
    24. Younis, Ijaz & Shah, Waheed Ullah & Yousaf, Imran, 2023. "Static and dynamic linkages between oil, gold and global equity markets in various crisis episodes: Evidence from the Wavelet TVP-VAR," Resources Policy, Elsevier, vol. 80(C).
    25. Uddin, Gazi Salah & Hernandez, Jose Areola & Shahzad, Syed Jawad Hussain & Hedström, Axel, 2018. "Multivariate dependence and spillover effects across energy commodities and diversification potentials of carbon assets," Energy Economics, Elsevier, vol. 71(C), pages 35-46.
    26. Cheng, Sheng & Han, Lingyu & Cao, Yan & Jiang, Qisheng & Liang, Ruibin, 2022. "Gold-oil dynamic relationship and the asymmetric role of geopolitical risks: Evidence from Bayesian pdBEKK-GARCH with regime switching," Resources Policy, Elsevier, vol. 78(C).
    27. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2020. "How connected is the carbon market to energy and financial markets? A systematic analysis of spillovers and dynamics," Energy Economics, Elsevier, vol. 90(C).
    28. Selva Demiralp & Kevin D. Hoover, 2003. "Searching for the Causal Structure of a Vector Autoregression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 745-767, December.
    29. Pilar Gargallo & Luis Lample & Jesús A. Miguel & Manuel Salvador, 2021. "Co-Movements between Eu Ets and the Energy Markets: A Var-Dcc-Garch Approach," Mathematics, MDPI, vol. 9(15), pages 1-36, July.
    30. Hu, Yang & Lang, Chunlin & Corbet, Shaen & Hou, Yang (Greg) & Oxley, Les, 2023. "Exploring the dynamic behaviour of commodity market tail risk connectedness during the negative WTI pricing event," Energy Economics, Elsevier, vol. 125(C).
    31. Abdul Rahman & Samir Saadi, 2008. "Random walk and breaking trend in financial series: An econometric critique of unit root tests," Review of Financial Economics, John Wiley & Sons, vol. 17(3), pages 204-212, August.
    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. Pakrooh, Parisa & Manera, Matteo, 2024. "Causality, Connectedness, and Volatility Pass-through among Energy-Metal-Stock-Carbon Markets: New Evidence from the EU," FEEM Working Papers 344790, Fondazione Eni Enrico Mattei (FEEM).
    2. Dai, Xingyu & Xiao, Ling & Wang, Qunwei & Dhesi, Gurjeet, 2021. "Multiscale interplay of higher-order moments between the carbon and energy markets during Phase III of the EU ETS," Energy Policy, Elsevier, vol. 156(C).
    3. Lovcha, Yuliya & Perez-Laborda, Alejandro & Sikora, Iryna, 2022. "The determinants of CO2 prices in the EU emission trading system," Applied Energy, Elsevier, vol. 305(C).
    4. Huang, Wenyang & Wang, Huiwen & Wei, Yigang, 2023. "Identifying the determinants of European carbon allowances prices: A novel robust partial least squares method for open-high-low-close data," International Review of Financial Analysis, Elsevier, vol. 90(C).
    5. Duan, Kun & Ren, Xiaohang & Shi, Yukun & Mishra, Tapas & Yan, Cheng, 2021. "The marginal impacts of energy prices on carbon price variations: Evidence from a quantile-on-quantile approach," Energy Economics, Elsevier, vol. 95(C).
    6. Gong, Xu & Shi, Rong & Xu, Jun & Lin, Boqiang, 2021. "Analyzing spillover effects between carbon and fossil energy markets from a time-varying perspective," Applied Energy, Elsevier, vol. 285(C).
    7. Yaqi Wu & Chen Zhang & Po Yun & Dandan Zhu & Wei Cao & Zulfiqar Ali Wagan, 2021. "Time–frequency analysis of the interaction mechanism between European carbon and crude oil markets," Energy & Environment, , vol. 32(7), pages 1331-1357, November.
    8. Adekoya, Oluwasegun B. & Oliyide, Johnson A. & Noman, Ambreen, 2021. "The volatility connectedness of the EU carbon market with commodity and financial markets in time- and frequency-domain: The role of the U.S. economic policy uncertainty," Resources Policy, Elsevier, vol. 74(C).
    9. Fang Zhang & Zhengjun Zhang, 2020. "The tail dependence of the carbon markets: The implication of portfolio management," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-17, August.
    10. Cristiano Salvagnin & Aldo Glielmo & Maria Elena De Giuli & Antonietta Mira, 2024. "Investigating the price determinants of the European Emission Trading System: a non-parametric approach," Papers 2406.05094, arXiv.org.
    11. Demiralay, Sercan & Gencer, Hatice Gaye & Bayraci, Selcuk, 2022. "Carbon credit futures as an emerging asset: Hedging, diversification and downside risks," Energy Economics, Elsevier, vol. 113(C).
    12. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2020. "How connected is the carbon market to energy and financial markets? A systematic analysis of spillovers and dynamics," Energy Economics, Elsevier, vol. 90(C).
    13. Li, Houjian & Li, Qingman & Huang, Xinya & Guo, Lili, 2023. "Do green bonds and economic policy uncertainty matter for carbon price? New insights from a TVP-VAR framework," International Review of Financial Analysis, Elsevier, vol. 86(C).
    14. Chen, Linfei & Zhao, Xuefeng, 2024. "A multiscale and multivariable differentiated learning for carbon price forecasting," Energy Economics, Elsevier, vol. 131(C).
    15. Qiao, Sen & Dang, Yi Jing & Ren, Zheng Yu & Zhang, Kai Quan, 2023. "The dynamic spillovers among carbon, fossil energy and electricity markets based on a TVP-VAR-SV method," Energy, Elsevier, vol. 266(C).
    16. Hanif, Waqas & Arreola Hernandez, Jose & Mensi, Walid & Kang, Sang Hoon & Uddin, Gazi Salah & Yoon, Seong-Min, 2021. "Nonlinear dependence and connectedness between clean/renewable energy sector equity and European emission allowance prices," Energy Economics, Elsevier, vol. 101(C).
    17. Chang, Kai & Ye, Zhifang & Wang, Weihong, 2019. "Volatility spillover effect and dynamic correlation between regional emissions allowances and fossil energy markets: New evidence from China’s emissions trading scheme pilots," Energy, Elsevier, vol. 185(C), pages 1314-1324.
    18. Wenjun Chu & Shanglei Chai & Xi Chen & Mo Du, 2020. "Does the Impact of Carbon Price Determinants Change with the Different Quantiles of Carbon Prices? Evidence from China ETS Pilots," Sustainability, MDPI, vol. 12(14), pages 1-19, July.
    19. Zhong, Meirui & Zhang, Rui & Ren, Xiaohang, 2023. "The time-varying effects of liquidity and market efficiency of the European Union carbon market: Evidence from the TVP-SVAR-SV approach," Energy Economics, Elsevier, vol. 123(C).
    20. Huang, Wenyang & Zhao, Jianyu & Wang, Xiaokang, 2024. "Model-driven multimodal LSTM-CNN for unbiased structural forecasting of European Union allowances open-high-low-close price," Energy Economics, Elsevier, vol. 132(C).

    More about this item

    Keywords

    Causality direction; Dependency structure; EU-ETS; Time-varying spillover;
    All these keywords.

    JEL classification:

    • O52 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Europe
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:fem:femwpa:2024.22. 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: Alberto Prina Cerai (email available below). General contact details of provider: https://edirc.repec.org/data/feemmit.html .

    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.