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Dynamic volatility spillover relationships between the Chinese carbon and international energy markets from extreme climate shocks

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  • Chen, Zhang-HangJian
  • Zhao, Shou-Yu
  • Song, Huai-Bing
  • Yang, Ming-Yuan
  • Li, Sai-Ping

Abstract

The immense attention to climate change risk has stimulated increasing interest in carbon markets and their linkages to other markets. This study investigates the dynamic volatility spillover relationships between the Chinese carbon and international energy markets, and the impact of extreme weather events on the relationships. Empirical results show that the risk is transferred from the international gas (GAS) and crude oil (OIL) markets to the Chinese carbon market (GDC). The total volatility spillover among markets and the net spillover of GDC with other markets both have obvious periodicity. The shocks from extreme weather events and extremely high temperatures can amplify the trading volume of GDC, and strengthen the fluctuations of GDC, ultimately turning GDC from a risk receiver to a risk transmitter. The portfolio strategies based on the reversal phenomenon can achieve higher average returns compared to the Chinese and EU carbon markets. In addition, the shocks of the Sino-US trade war, the Covid-19 outbreak, the COP 26 and the Russo-Ukrainian war have different effects on the volatility spillovers among markets. Economic and policy implications for investors and regulators are also provided along with these findings.

Suggested Citation

  • Chen, Zhang-HangJian & Zhao, Shou-Yu & Song, Huai-Bing & Yang, Ming-Yuan & Li, Sai-Ping, 2024. "Dynamic volatility spillover relationships between the Chinese carbon and international energy markets from extreme climate shocks," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 626-645.
  • Handle: RePEc:eee:reveco:v:92:y:2024:i:c:p:626-645
    DOI: 10.1016/j.iref.2024.02.005
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    More about this item

    Keywords

    Volatility spillover; Carbon market; Energy markets; Exogenous shocks; Extreme weather;
    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
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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