国际油价对中国能源金属金融市场高阶尾部依赖影响
The Impact of International Oil Prices on the Higher-Order Tail Dependence of China’s Energy-Metal Financial Markets
摘要: 随着全球能源市场波动加剧，国际油价对中国能源金属金融市场的高阶矩尾部关联性及风险传导机制产生了显著影响。本研究基于2005~2024年每日数据，采用高阶矩风险测度、分位数VAR网络和分位数对分位数回归等方法，构建涵盖传统能源、新能源与金属市场的多维体系，系统分析国际油价在不同分位数下对收益率、波动率、偏度和峰度尾部关联的动态效应。结果显示，能源金属市场收益分布呈“尖峰厚尾”和显著偏态，风险传导呈“U形”结构，极端情况下总溢出指数高达80%~90%；传统能源和有色金属是净溢出源，而新能源和稀土是净接收者。国际油价的极端波动对尾部关联性具有明显非对称效应。研究结论可为可持续投资组合构建、绿色能源风险管理提供重要参考。
Abstract: As global energy market volatility intensifies and China advances its sustainable energy transition, international oil prices exert significant influences on the higher-moment tail dependence and risk transmission of China’s energy-metal financial markets. Using daily data from 2005~2024, this study employs higher-moment risk measures, quantile VAR networks, and quantile-on-quantile regression to construct a multi-dimensional framework covering traditional energy, new energy, and metal markets. We analyze the dynamic effects of oil prices on tail dependence in returns, volatility, skewness, and kurtosis across different quantiles and capture time-varying spillovers under major events through rolling-window estimation. The results reveal fat-tailed and skewed return distributions, a U-shaped spillover pattern, and extreme-state total spillovers reaching 80%~90%. Traditional energy and base metals act as net transmitters, while new energy and rare earths are net receivers. Extreme oil price shocks show clear asymmetry, with crashes weakening low-tail dependence and surges strengthening high-tail dependence. These findings provide important evidence for sustainable portfolio construction, green-energy risk management, and policymaking in support of China’s energy transition.
文章引用：何佳, 马昕乐. 国际油价对中国能源金属金融市场高阶尾部依赖影响[J]. 可持续发展, 2026, 16(1): 318-331. https://doi.org/10.12677/sd.2026.161037

参考文献

[1] Zhou, Y., Wu, S., Liu, Z. and Rognone, L. (2023) The Asymmetric Effects of Climate Risk on Higher-Moment Connectedness among Carbon, Energy and Metals Markets. Nature Communications, 14, Article No. 7157. [Google Scholar] [CrossRef] [PubMed]
[2] Ji, Q. and Guo, J. (2015) Oil Price Volatility and Oil-Related Events: An Internet Concern Study Perspective. Applied Energy, 137, 256-264. [Google Scholar] [CrossRef] 
[3] Wu, F., Zhang, D. and Ji, Q. (2021) Systemic Risk and Financial Contagion across Top Global Energy Companies. Energy Economics, 97, Article ID: 105221. [Google Scholar] [CrossRef] 
[4] Ji, Q., Zhang, D. and Zhang, Z. (2023) Energy Market Financialization, Integration and Systemic Risks. Energy Economics, 117, Article ID: 106448. [Google Scholar] [CrossRef] 
[5] Perera, A.T.D., Nik, V.M., Chen, D., Scartezzini, J. and Hong, T. (2020) Quantifying the Impacts of Climate Change and Extreme Climate Events on Energy Systems. Nature Energy, 5, 150-159. [Google Scholar] [CrossRef] 
[6] Shao, L. and Zhang, H. (2020) The Impact of Oil Price on the Clean Energy Metal Prices: A Multi-Scale Perspective. Resources Policy, 68, Article ID: 101730. [Google Scholar] [CrossRef] 
[7] Sun, X., Fang, W., Gao, X., An, H., Si, J. and Wei, H. (2024) Dynamic Interactions among New Energy Metals and Price Adjustment Strategies: A Cross-Industry Chain Perspective. Energy, 303, Article ID: 131923. [Google Scholar] [CrossRef] 
[8] Zhu, X., Liao, J. and Chen, Y. (2021) Time-Varying Effects of Oil Price Shocks and Economic Policy Uncertainty on the Nonferrous Metals Industry: From the Perspective of Industrial Security. Energy Economics, 97, Article ID: 105192. [Google Scholar] [CrossRef] 
[9] Hoffart, F.M., D’Orazio, P., Holz, F. and Kemfert, C. (2024) Exploring the Interdependence of Climate, Finance, Energy, and Geopolitics: A Conceptual Framework for Systemic Risks Amidst Multiple Crises. Applied Energy, 361, Article ID: 122885. [Google Scholar] [CrossRef] 
[10] Mahmoud, I. (2025) Time-varying Efficiency in Spot and Future Energy Markets and Precious Metals: An Econophysics Approach. Risk and Decision Analysis, 11, 50-61. [Google Scholar] [CrossRef] 
[11] Umar, M., Riaz, Y. and Yousaf, I. (2022) Impact of Russian-Ukraine War on Clean Energy, Conventional Energy, and Metal Markets: Evidence from Event Study Approach. Resources Policy, 79, Article ID: 102966. [Google Scholar] [CrossRef] 
[12] Li, H., Li, Y. and Zhang, H. (2023) The Spillover Effects among the Traditional Energy Markets, Metal Markets and Sub-Sector Clean Energy Markets. Energy, 275, Article ID: 127384. [Google Scholar] [CrossRef] 
[13] Zhang, C. and Tu, X. (2016) The Effect of Global Oil Price Shocks on China’s Metal Markets. Energy Policy, 90, 131-139. [Google Scholar] [CrossRef] 
[14] Dutta, A. (2018) Impacts of Oil Volatility Shocks on Metal Markets: A Research Note. Resources Policy, 55, 9-19. [Google Scholar] [CrossRef] 
[15] Wang, X. (2022) Efficient Markets Are More Connected: An Entropy-Based Analysis of the Energy, Industrial Metal and Financial Markets. Energy Economics, 111, Article ID: 106067. [Google Scholar] [CrossRef] 
[16] Tiwari, A.K., Pathak, R., DasGupta, R. and Sadorsky, P. (2021) Modelling Dependence and Systemic Risk between Oil Prices and BSE Sectoral Indices Using Stochastic Copula and Covar, δCoVar and MES Approaches. Applied Economics, 53, 6770-6788. [Google Scholar] [CrossRef] 
[17] Chu, W., Fan, L. and Zhou, P. (2024) Extreme Spillovers across Carbon and Energy Markets: A Multiscale Higher-Order Moment Analysis. Energy Economics, 138, Article ID: 107833. [Google Scholar] [CrossRef] 
[18] Liu, X., Wang, B., Luo, M., et al. (2025) The Dynamic Risk Spillover of Higher-Order Moments in the China’s Energy Market: A Time-Frequency Perspective. International Journal of Green Energy, 22, 2010-2028.
[19] Liu, J. (2021) A New Tail-Based Correlation Measure and Its Application in Global Equity Markets. Journal of Financial Econometrics, 21, 959-987. [Google Scholar] [CrossRef] 
[20] Wu, R., Li, B. and Qin, Z. (2024) Spillovers and Dependency between Green Finance and Traditional Energy Markets under Different Market Conditions. Energy Policy, 192, Article ID: 114263. [Google Scholar] [CrossRef] 
[21] Lin, B. and Zhang, Z. (2025) Extreme Spillovers among Green Finance, Energy, and Energy Metals Markets in China: Evidence under the Dilemma of Energy Transition. Renewable Energy, 241, Article ID: 122403. [Google Scholar] [CrossRef] 
[22] Ke, R., Shen, A., Yin, M. and Tan, C. (2024) The Cross-Sector Risk Contagion among Chinese Financial Institutions: Evidence from the Extreme Volatility Spillover Perspective. Finance Research Letters, 63, Article ID: 105303. [Google Scholar] [CrossRef] 
[23] Cai, Y., Zhang, Y. and Zhang, A. (2025) Oil Price Shocks and Airlines Stock Return and Volatility—A GFEVD Analysis. Economics of Transportation, 41, Article ID: 100396. [Google Scholar] [CrossRef] 
[24] Ayoub, M. and Qadan, M. (2024) Financial Ambiguity and Oil Prices. Financial Innovation, 10, Article Number 137. [Google Scholar] [CrossRef] 
[25] Lahiani, A., Miloudi, A., Benkraiem, R. and Shahbaz, M. (2017) Another Look on the Relationships between Oil Prices and Energy Prices. Energy Policy, 102, 318-331. [Google Scholar] [CrossRef] 
[26] Broadstock, D.C., Wang, R. and Zhang, D. (2014) Direct and Indirect Oil Shocks and Their Impacts Upon Energy Related Stocks. Economic Systems, 38, 451-467. [Google Scholar] [CrossRef] 
[27] Zhou, E. and Wang, X. (2023) Dynamics of Systemic Risk in European Gas and Oil Markets under the Russia-Ukraine Conflict: A Quantile Regression Neural Network Approach. Energy Reports, 9, 3956-3966.
[28] Fu, Z., Chen, Z., Sharif, A. and Razi, U. (2022) The Role of Financial Stress, Oil, Gold and Natural Gas Prices on Clean Energy Stocks: Global Evidence from Extreme Quantile Approach. Resources Policy, 78, Article ID: 102860. [Google Scholar] [CrossRef] 
[29] Zaghdoudi, T., Tissaoui, K., Maaloul, M.H., Bahou, Y. and Kammoun, N. (2023) Asymmetric Connectedness between Oil Price, Coal and Renewable Energy Consumption in China: Evidence from Fourier NARDL Approach. Energy, 285, Article ID: 129416. [Google Scholar] [CrossRef] 
[30] Zhou, D., Siddik, A.B., Guo, L. and Li, H. (2023) Dynamic Relationship among Climate Policy Uncertainty, Oil Price and Renewable Energy Consumption—Findings from TVP-SV-VAR Approach. Renewable Energy, 204, 722-732. [Google Scholar] [CrossRef] 
[31] Chen, J., Liang, Z., Ding, Q. and Liu, Z. (2022) Extreme Spillovers among Fossil Energy, Clean Energy, and Metals Markets: Evidence from a Quantile-Based Analysis. Energy Economics, 107, Article ID: 105880. [Google Scholar] [CrossRef] 
[32] Li, Z., Li, Y., Huang, C. and Peculea, A.D. (2023) Volatility Spillover across Chinese Carbon Markets: Evidence from Quantile Connectedness Method. Energy Economics, 119, Article ID: 106542. [Google Scholar] [CrossRef] 
[33] Sim, N. and Zhou, H. (2015) Oil Prices, US Stock Return, and the Dependence between Their Quantiles. Journal of Banking & Finance, 55, 1-8. [Google Scholar] [CrossRef] 
[34] Silvério, R. and Szklo, A. (2012) The Effect of the Financial Sector on the Evolution of Oil Prices: Analysis of the Contribution of the Futures Market to the Price Discovery Process in the WTI Spot Market. Energy Economics, 34, 1799-1808. [Google Scholar] [CrossRef] 
[35] Xing, X., Xu, Z., Chen, Y., Ouyang, W., Deng, J. and Pan, H. (2023) The Impact of the Russia-Ukraine Conflict on the Energy Subsector Stocks in China: A Network-Based Approach. Finance Research Letters, 53, Article ID: 103645. [Google Scholar] [CrossRef] 
[36] Klotz, P., Lin, T.C. and Hsu, S.-H. (2014) Global Commodity Prices, Economic Activity and Monetary Policy: The Relevance of China. Resources Policy, 42, 1-9. [Google Scholar] [CrossRef] 
[37] Li, Y., Niu, T. and Wang, X. (2023) Exploration of Industrial Risk Contagion Characteristics and Mechanism under Geopolitical Events: Evidence from China. Applied Economics, 56, 3582-3599. [Google Scholar] [CrossRef] 
[38] Jia, Z., Wen, S. and Lin, B. (2021) The Effects and Reacts of COVID-19 Pandemic and International Oil Price on Energy, Economy, and Environment in China. Applied Energy, 302, Article ID: 117612. [Google Scholar] [CrossRef] [PubMed]

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