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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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    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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