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Asymmetric and time-frequency volatility connectedness between China and international crude oil markets with portfolio implications

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  • Liu, Zhenhua
  • Ji, Qiang
  • Zhai, Pengxiang
  • Ding, Zhihua

Abstract

This paper tries to examine asymmetric and time-frequency volatility connectedness between the Chinese crude oil futures market and international oil benchmarks. To this end, we separate the realized volatility as bad or good volatility and decompose the aggregate volatility connectedness among these oil markets into the short-, medium-, and long-term components. Our results first show that these crude oil markets are highly connected, whereas the Chinese crude oil futures market is a net receiver in the volatility system. Second, the spillover effect caused by bad volatility is significantly different from that of good volatility, revealing significant asymmetry in the volatility spillovers. Third, the volatility spillovers in the short-term frequency band account for the most of total volatility spillovers. Finally, our results prove that the volatility connectedness information among different oil markets helps design trading strategies and shed light on the arbitrage opportunities in the Chinese new crude oil futures market.

Suggested Citation

  • Liu, Zhenhua & Ji, Qiang & Zhai, Pengxiang & Ding, Zhihua, 2023. "Asymmetric and time-frequency volatility connectedness between China and international crude oil markets with portfolio implications," Research in International Business and Finance, Elsevier, vol. 66(C).
    • Handle: RePEc:eee:riibaf:v:66:y:2023:i:c:s0275531923001654
    DOI: 10.1016/j.ribaf.2023.102039
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    References listed on IDEAS

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    1. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    2. Nishimura, Yusaku & Sun, Bianxia, 2018. "The intraday volatility spillover index approach and an application in the Brexit vote," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 241-253.
    3. Sun, Xiaolei & Chen, Xiuwen & Wang, Jun & Li, Jianping, 2020. "Multi-scale interactions between economic policy uncertainty and oil prices in time-frequency domains," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    4. Weiner, R.J., 1991. "Is the World Oil Market "One Great Pool?"," Papers 9120, Laval - Recherche en Energie.
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    Citations

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    Cited by:

    1. Mensi, Walid & Ahmadian-Yazdi, Farzaneh & Al-Kharusi, Sami & Roudari, Soheil & Kang, Sang Hoon, 2024. "Extreme Connectedness Across Chinese Stock and Commodity Futures Markets," Research in International Business and Finance, Elsevier, vol. 70(PA).
    2. Kočenda, Evžen & Moravcová, Michala, 2024. "Frequency volatility connectedness and portfolio hedging of U.S. energy commodities," Research in International Business and Finance, Elsevier, vol. 69(C).
    3. Wen, Danyan & Wang, Huihui & Wang, Yudong & Xiao, Jihong, 2024. "Crude oil futures and the short-term price predictability of petroleum products," Energy, Elsevier, vol. 307(C).
    4. Cui, Jinxin & Alshater, Muneer M. & Mensi, Walid, 2023. "Higher-order moment risk spillovers and optimal portfolio strategies in global oil markets," Resources Policy, Elsevier, vol. 86(PA).
    5. Zhu, Bangzhu & Tian, Chao & Wang, Ping, 2024. "Exploring the relationship between Chinese crude oil futures market efficiency and market micro characteristics," Energy Economics, Elsevier, vol. 134(C).

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    More about this item

    Keywords

    Oil market; Time-frequency domain; Volatility spillovers; High-frequency data; Trading strategy;
    All these keywords.

    JEL classification:

    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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