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The spillover effect between Chinese crude oil futures market and Chinese green energy stock market

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  • Li, Jingpeng
  • Umar, Muhammad
  • Huo, Jiale

Abstract

With the increasing severe pollution, the new energy industry is greatly favored by the government and investors. Using the static network connectedness method of Diebold and Yilmaz (2009, 2012, 2014) and the dynamic network connectedness approach of Antonakakis et al. (2020), this paper discusses the return and volatility spillover effects between China's crude oil futures market and 7 Chinese green energy stock markets. In terms of return spillover effects, we find firstly that Chinese green energy stock is able to dominate the price changes in the crude oil market, and the dominate role of natural gas stock market is stronger. Secondly, rather than changing the dominant role of the green energy stock market on crude oil futures market price changes, the outbreak of COVID-19 in 2020 strengthened that dominant role. For the volatility spillover effects, the results of static volatility spillover index show that the crude oil futures market volatility is mainly dominated by the green energy equity market, but the dynamic connectedness indices results show that the volatility in the international energy market can strengthen the dominant role of the crude oil futures on the volatility of the green energy stock market. Finally, we can find that both the outbreak of COVID-19 in 2020 and the online operation of the Chinese carbon trading market in 2021 can strengthen the dominant role of the green energy stock market on the crude oil futures market volatility.

Suggested Citation

  • Li, Jingpeng & Umar, Muhammad & Huo, Jiale, 2023. "The spillover effect between Chinese crude oil futures market and Chinese green energy stock market," Energy Economics, Elsevier, vol. 119(C).
    • Handle: RePEc:eee:eneeco:v:119:y:2023:i:c:s014098832300066x
    DOI: 10.1016/j.eneco.2023.106568
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    More about this item

    Keywords

    Static network connectedness; Dynamic network connectedness; Crude oil; Green energy stock market; Spillover;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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