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Exploring the dynamic behaviour of commodity market tail risk connectedness during the negative WTI pricing event

Author

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  • Hu, Yang
  • Lang, Chunlin
  • Corbet, Shaen
  • Hou, Yang (Greg)
  • Oxley, Les
Abstract
Using a TVP-VAR analytical framework, this study explores the change and persistence of the dynamic connectedness of international energy and carbon credit markets. The overall destabilising effects generated by recent political and epidemiological events, and the subsequent consequences of shocks such as the negative WTI pricing event, have the potential to be disruptive to the continued growth and development of several regional oil markets. Results are presented via a comprehensive analysis of the dynamics of extreme risk spillovers for particular commodity pairs. In particular, WTI and Brent crude oil are found to have transmitted significant tail uncertainty shocks to other energy markets. However, Shanghai crude oil and carbon credit markets typically function as shock absorbers. The remaining energy-related commodities primarily function as tail uncertainty receivers. Further, by incorporating EGARCH-based robustness procedures, tests for significant market connectedness within international energy markets adds further validity to the results. Specifically, results relating to the substantial rebalancing of information to Shanghai crude oil futures and EUA carbon futures merit special consideration, as dynamic interactions strengthen evidence supporting their continued maturation into significant international markets. These findings are particularly interesting to policymakers and market participants who use such products to hedge against and diversify regional oil market fluctuations.

Suggested Citation

  • Hu, Yang & Lang, Chunlin & Corbet, Shaen & Hou, Yang (Greg) & Oxley, Les, 2023. "Exploring the dynamic behaviour of commodity market tail risk connectedness during the negative WTI pricing event," Energy Economics, Elsevier, vol. 125(C).
    • Handle: RePEc:eee:eneeco:v:125:y:2023:i:c:s0140988323003274
    DOI: 10.1016/j.eneco.2023.106829
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    Cited by:

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    4. Tang, Yusui & Zhong, Juandan, 2023. "Predicting gold volatility: Exploring the impact of extreme risk in the international commodity market," Finance Research Letters, Elsevier, vol. 58(PB).
    5. Xuewei Zhou & Zisheng Ouyang & Rangan Gupta & Qiang Ji, 2024. "Time-Varying Multilayer Networks Analysis of Frequency Connectedness in Commodity Futures Markets," Working Papers 202422, University of Pretoria, Department of Economics.
    6. Pakrooh, Parisa & Manera, Matteo, 2024. "Causality, Connectedness, and Volatility Pass-through among Energy-Metal-Stock-Carbon Markets: New Evidence from the EU," FEEM Working Papers 344790, Fondazione Eni Enrico Mattei (FEEM).
    7. Parisa Pakrooh & Matteo Manera, 2024. "Causality, Connectedness, and Volatility Pass-through among Energy-Metal-Stock-Carbon Markets: New Evidence from the EU," Working Papers 2024.22, Fondazione Eni Enrico Mattei.

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    More about this item

    Keywords

    TVP-VAR; Dynamic connectedness; Oil markets; EGARCH; Negative valuation;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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