Green finance and hedging in U.S. energy markets: evidence on volatility and policy insights

In this study, we investigate the relationship between crude oil prices and green and grey energy exchange-traded funds (ETFs). We use the Dynamic Conditional Correlation Generalized Autoregressive Conditional Heteroskedasticity (DCC-GARCH) model to estimate time-varying correlations and hedge ratios by using monthly data from 2008 to 2024. The findings show that the green energy ETF market experiences volatility spillovers from grey markets, suggesting that these investments are not isolated from the risks present in traditional energy markets. Hedging with oil futures or grey ETFs can reduce portfolio risk by 32% to 45%. Additionally, we conduct a comparative analysis of the hedging tools in terms of their effectiveness, including fossil fuel-based, broad market, and ESG-oriented hedging instruments. We find that inverse ETFs and oil derivatives are among the most effective tools for mitigating risk exposure. The research results enable us to develop specific recommendations that investors and policymakers can use to enhance green investment resilience through ESG-aligned derivative development and investment strategy implementation of dynamic risk management systems.

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Publication Details

Journal
Academia green energy.
Published
2025-11-27
DOI
https://doi.org/10.20935/acadenergy8014
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
0.00
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article

Green finance and hedging in U.S. energy markets: evidence on volatility and policy insights

Selahattin Bekmez, Syed Riaz Mahmood Ali, Enrika Huseni
Academia green energy.
Market Dynamics and Volatility
article

Green finance and hedging in U.S. energy markets: evidence on volatility and policy insights

Selahattin Bekmez, Syed Riaz Mahmood Ali, Enrika Huseni
article en

Abstract

In this study, we investigate the relationship between crude oil prices and green and grey energy exchange-traded funds (ETFs). We use the Dynamic Conditional Correlation Generalized Autoregressive Conditional Heteroskedasticity (DCC-GARCH) model to estimate time-varying correlations and hedge ratios by using monthly data from 2008 to 2024. The findings show that the green energy ETF market experiences volatility spillovers from grey markets, suggesting that these investments are not isolated from the risks present in traditional energy markets. Hedging with oil futures or grey ETFs can reduce portfolio risk by 32% to 45%. Additionally, we conduct a comparative analysis of the hedging tools in terms of their effectiveness, including fossil fuel-based, broad market, and ESG-oriented hedging instruments. We find that inverse ETFs and oil derivatives are among the most effective tools for mitigating risk exposure. The research results enable us to develop specific recommendations that investors and policymakers can use to enhance green investment resilience through ESG-aligned derivative development and investment strategy implementation of dynamic risk management systems.

Academia green energy.Vol. 2(4)
North American University (US)
Openalex Percentile: Top 56%
Market Dynamics and Volatility
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