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Dynamic Connectedness Among Energy Markets and EUA Climate Credit: The Role of GPR and VIX

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  • Maria Leone

    (Department of Management, Polytechnic University of Marche, Piazzale Martelli 8, 60121 Ancona, Italy)

  • Alberto Manelli

    (Department of Management, Polytechnic University of Marche, Piazzale Martelli 8, 60121 Ancona, Italy)

  • Roberta Pace

    (Department of Industrial and Information Engineering and Economics, University of L’Aquila, Via G. Mezzanotte, 67100 L’Aquila, Italy)

Abstract

Energy raw materials are the basis of the economic system. From this emerges the need to examine in more detail how various uncertainty indices interact with the dynamic of spillover connectedness among energy markets. The TVP-VAR model is used to investigate connectedness among US, European, and Indian oil and gas markets and the S&P carbon allowances Eua index. Following this, the wavelet decomposition technique is used to capture the dynamic correlations between uncertainty indices (GPR and VIX) and connectedness indices. First, the results indicate that energy market spillovers are time-varying and crisis-sensitive. Second, the time–frequency dependence among uncertainty indices and connectedness indices is more marked and can change with the occurrence of unexpected events and geopolitical conflicts. The VIX index shows a positive dependence on total dynamic connectedness in the mid-long-term, while the GPR index has a long-term effect only after 2020. The analysis of the interdependence among the connectedness of each market and the uncertainty indices is more heterogeneous. Political tensions and geopolitical risks are, therefore, causal factors of energy prices. Given their strategic and economic importance, policy makers and investors should establish a risk warning mechanism and try to avoid the transmission of spillovers as much as possible.

Suggested Citation

  • Maria Leone & Alberto Manelli & Roberta Pace, 2025. "Dynamic Connectedness Among Energy Markets and EUA Climate Credit: The Role of GPR and VIX," JRFM, MDPI, vol. 18(8), pages 1-17, August.
  • Handle: RePEc:gam:jjrfmx:v:18:y:2025:i:8:p:462-:d:1728160
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    References listed on IDEAS

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    1. Su, Chi-Wei & Khan, Khalid & Tao, Ran & Nicoleta-Claudia, Moldovan, 2019. "Does geopolitical risk strengthen or depress oil prices and financial liquidity? Evidence from Saudi Arabia," Energy, Elsevier, vol. 187(C).
    2. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    3. Mo, Bin & Nie, He & Zhao, Rongjie, 2024. "Dynamic nonlinear effects of geopolitical risks on commodities: Fresh evidence from quantile methods," Energy, Elsevier, vol. 288(C).
    4. Spyros Papathanasiou & Drosos Koutsokostas, 2024. "A trade-off between sustainability ratings and volatility in portfolio hedging strategies," International Journal of Banking, Accounting and Finance, Inderscience Enterprises Ltd, vol. 14(3), pages 370-406.
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