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The Influence of Financial Stress on Dynamic Connectedness between Fossil Energy Commodities and Green Energy Markets

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  • Pınar Evrim Mandacı
  • Birce Tedik Kocakaya
  • Efe Çağlar Çağlı
  • Dilvin Taşkın

Abstract

This paper aims to examine the impacts of selected stress variables, such as FSI (Financial Stress Index), VIX (Volatility Index), and EPU (Economic Policy Uncertainty), on dynamic connectedness between green markets (stocks and bonds) and fossil energy commodities. First, we employ the TVP-VAR model to measure connectedness. Then, the Fourier Cumulative Granger Causality test will be used to investigate the impacts of these stress variables on this connectedness from November 1, 2012, to November 15, 2022. The results indicate moderate return connectedness between these, mainly from short-term dynamics, suggesting that diversification may be more beneficial for long-term investments. In addition, the results indicate high connectedness during the COVID-19 pandemic. The results show high connectedness among fossil energy commodities but low connectedness among green stock and green bond markets, except for water company stocks. We observe a more significant impact of water stocks on markets, followed by oil. Our causality test results indicate that the FSI and VIX impact the connectedness between these two markets, but the connectedness influences all variables. Our results provide important implications for investors and policymakers.

Suggested Citation

  • Pınar Evrim Mandacı & Birce Tedik Kocakaya & Efe Çağlar Çağlı & Dilvin Taşkın, 2025. "The Influence of Financial Stress on Dynamic Connectedness between Fossil Energy Commodities and Green Energy Markets," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, vol. 10(2), pages 444-466.
    • Handle: RePEc:ahs:journl:v:10:y:2025:i:2:p:444-466
    DOI: 10.30784/epfad.1614216
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    References listed on IDEAS

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    1. Andrew Ang & Geert Bekaert, 2002. "International Asset Allocation With Regime Shifts," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1137-1187.
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    3. Naeem, Muhammad Abubakr & Nguyen, Thi Thu Ha & Nepal, Rabindra & Ngo, Quang-Thanh & Taghizadeh–Hesary, Farhad, 2021. "Asymmetric relationship between green bonds and commodities: Evidence from extreme quantile approach," Finance Research Letters, Elsevier, vol. 43(C).
    4. Saeed, Tareq & Bouri, Elie & Alsulami, Hamed, 2021. "Extreme return connectedness and its determinants between clean/green and dirty energy investments," Energy Economics, Elsevier, vol. 96(C).
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    Keywords

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    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
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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