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Does carbon price volatility affect European stock market sectors? A connectedness network analysis

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  • Aslan, Aydin
  • Posch, Peter N.

Abstract

We investigate how the volatility of carbon emission allowance (EUA) prices affects European stock market sectors. We employ a connectedness network analysis on prices of EUA futures and FTSE stock market sector indices and find that the EUA is mostly a net receiver of volatility connectedness and significantly receives volatility across most sectors during the recent European energy crisis.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:finlet:v:50:y:2022:i:c:s1544612322004974
    DOI: 10.1016/j.frl.2022.103318
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    References listed on IDEAS

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    1. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    2. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
    3. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    4. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
    5. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    6. Francis X. Diebold & Kamil Yilmaz, 2016. "Trans-Atlantic Equity Volatility Connectedness: U.S. and European Financial Institutions, 2004–2014," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 81-127.
    7. 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.
    8. Hintermayer, Martin, 2020. "A Carbon Price Floor in the Reformed EU ETS: Design Matters!," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224576, Verein für Socialpolitik / German Economic Association.
    9. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    10. Hintermayer, Martin, 2020. "A carbon price floor in the reformed EU ETS: Design matters!," Energy Policy, Elsevier, vol. 147(C).
    11. Hintermayer, Martin, 2020. "A Carbon Price Floor in the Reformed EU ETS: Design matters!," EWI Working Papers 2020-3, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
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    Cited by:

    1. Suleman, Muhammad Tahir & Rehman, Mobeen Ur & Sheikh, Umaid A. & Kang, Sang Hoon, 2023. "Dynamic time-frequency connectedness between European emissions trading system and sustainability markets," Energy Economics, Elsevier, vol. 123(C).
    2. Chao Zhang & Yihang Zhao & Huiru Zhao, 2022. "A Novel Hybrid Price Prediction Model for Multimodal Carbon Emission Trading Market Based on CEEMDAN Algorithm and Window-Based XGBoost Approach," Mathematics, MDPI, vol. 10(21), pages 1-16, November.
    3. Zhao, Lu-Tao & Liu, Hai-Yi & Chen, Xue-Hui, 2024. "How does carbon market interact with energy and sectoral stocks? Evidence from risk spillover and wavelet coherence," Journal of Commodity Markets, Elsevier, vol. 33(C).
    4. 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).
    5. 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.

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    More about this item

    Keywords

    EU ETS; EUA; Connectedness network; Volatility spillover;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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