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Portfolio selection from risk transfer mechanisms in a time of crisis for renewable energy markets

Author

Listed:
  • Yu-Ann Wang

    (Taiwan Research Institute, Taiwan)

  • Chia-Lin Chang

    (National Chung Hsing University, Taiwan)

Abstract

This study explores risk transmission in financial markets, focusing on investor hedging decisions. It examines risk movement between renewable and fossil fuel energy assets in energy ETFs during the Global Financial Crisis (GFC) and the COVID-19 pandemic. A novel test evaluates how an energy asset's volatility impacts the overall portfolio risk, offering insights for managing financial risk. The analysis covers three major renewable energy ETFs (solar, wind, and hydro) and three fossil fuel ETFs (oil, coal, and natural gas). During the COVID-19 crisis, effective combinations such as (solar, coal) and (wind, coal) are recommended for minimizing losses. Although not ideal for hedging solar-related risks, (solar, oil) is advantageous for oil-related shocks. The study found that combining solar with oil and wind with oil was effective in mitigating losses during the GFC and before COVID-19. In non-pandemic periods, combinations like (solar, oil) or (solar, coal) are valuable for risk management. This research highlights the interconnectedness of energy assets and provides actionable insights for investors and policymakers. Future research could examine other events, like the Russia-Ukraine war, impacting global energy markets.

Suggested Citation

  • Yu-Ann Wang & Chia-Lin Chang, 2024. "Portfolio selection from risk transfer mechanisms in a time of crisis for renewable energy markets," KIER Working Papers 1108, Kyoto University, Institute of Economic Research.
  • Handle: RePEc:kyo:wpaper:1108
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    References listed on IDEAS

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    1. Syed Kumail Abbas Rizvi & Bushra Naqvi & Nawazish Mirza, 2022. "Is green investment different from grey? Return and volatility spillovers between green and grey energy ETFs," Annals of Operations Research, Springer, vol. 313(1), pages 495-524, June.
    2. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    3. Reboredo, Juan C., 2015. "Is there dependence and systemic risk between oil and renewable energy stock prices?," Energy Economics, Elsevier, vol. 48(C), pages 32-45.
    4. Managi, Shunsuke & Okimoto, Tatsuyoshi, 2013. "Does the price of oil interact with clean energy prices in the stock market?," Japan and the World Economy, Elsevier, vol. 27(C), pages 1-9.
    5. Michael McAleer, 2019. "What They Did Not Tell You about Algebraic (Non-) Existence, Mathematical (IR-)Regularity, and (Non-) Asymptotic Properties of the Dynamic Conditional Correlation (DCC) Model," JRFM, MDPI, vol. 12(2), pages 1-9, April.
    6. Troster, Victor & Shahbaz, Muhammad & Uddin, Gazi Salah, 2018. "Renewable energy, oil prices, and economic activity: A Granger-causality in quantiles analysis," Energy Economics, Elsevier, vol. 70(C), pages 440-452.
    7. Chia-Lin Chang & Michael McAleer & Jiarong Tian, 2019. "Modeling and Testing Volatility Spillovers in Oil and Financial Markets for the USA, the UK, and China," Energies, MDPI, vol. 12(8), pages 1-24, April.
    8. Michael McAleer, 2019. "What They Did Not Tell You about Algebraic (Non-) Existence, Mathematical (IR-)Regularity and (Non-) Asymptotic Properties of the Full BEKK Dynamic Conditional Covariance Model," JRFM, MDPI, vol. 12(2), pages 1-7, April.
    9. Arkady Gevorkyan, 2017. "Renewable versus nonrenewable resources: an analysis of volatility in futures prices," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 61(1), pages 19-35, January.
    10. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    11. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    12. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    13. Michael McAleer & Suhejla Hoti & Felix Chan, 2009. "Structure and Asymptotic Theory for Multivariate Asymmetric Conditional Volatility," Econometric Reviews, Taylor & Francis Journals, vol. 28(5), pages 422-440.
    14. Gevorkyan, Arkady, 2017. "Renewable versus nonrenewable resources: an analysis of volatility in futures prices," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 61(1), January.
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    More about this item

    Keywords

    Renewable energy; Volatility spillover; Risk Transfer; GFC; COVID-19;
    All these keywords.

    JEL classification:

    • 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
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G01 - Financial Economics - - General - - - Financial Crises
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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