IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v119y2023ics014098832300066x.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S014098832300066X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2023.106568?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Caporale, Guglielmo Maria & Menla Ali, Faek & Spagnolo, Nicola, 2015. "Oil price uncertainty and sectoral stock returns in China: A time-varying approach," China Economic Review, Elsevier, vol. 34(C), pages 311-321.
    2. Bouri, Elie & Cepni, Oguzhan & Gabauer, David & Gupta, Rangan, 2021. "Return connectedness across asset classes around the COVID-19 outbreak," International Review of Financial Analysis, Elsevier, vol. 73(C).
    3. 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.
    4. Adekoya, Oluwasegun B. & Akinseye, Ademola B. & Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Gabauer, David & Oliyide, Johnson, 2022. "Crude oil and Islamic sectoral stocks: Asymmetric TVP-VAR connectedness and investment strategies," Resources Policy, Elsevier, vol. 78(C).
    5. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    6. Liu, Zhenhua & Tseng, Hui-Kuan & Wu, Jy S. & Ding, Zhihua, 2020. "Implied volatility relationships between crude oil and the U.S. stock markets: Dynamic correlation and spillover effects," Resources Policy, Elsevier, vol. 66(C).
    7. Huang, Shupei & An, Haizhong & Gao, Xiangyun & Huang, Xuan, 2015. "Identifying the multiscale impacts of crude oil price shocks on the stock market in China at the sector level," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 434(C), pages 13-24.
    8. Chen, Yufeng & Zheng, Biao & Qu, Fang, 2020. "Modeling the nexus of crude oil, new energy and rare earth in China: An asymmetric VAR-BEKK (DCC)-GARCH approach," Resources Policy, Elsevier, vol. 65(C).
    9. Abdelmajid Hmaittane & Kais Bouslah & Bouchra M’Zali, 2019. "Does corporate social responsibility affect the cost of equity in controversial industry sectors?," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 18(4), pages 635-662, July.
    10. Sitara Karim & Muhammad Abubakr Naeem & Nawazish Mirza & Jessica Paule-Vianez, 2022. "Quantifying the hedge and safe-haven properties of bond markets for cryptocurrency indices," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 23(2), pages 191-205, January.
    11. Antonakakis, Nikolaos & Gabauer, David & Gupta, Rangan & Plakandaras, Vasilios, 2018. "Dynamic connectedness of uncertainty across developed economies: A time-varying approach," Economics Letters, Elsevier, vol. 166(C), pages 63-75.
    12. Ågren, Martin, 2006. "Does Oil Price Uncertainty Transmit to Stock Markets?," Working Paper Series 2006:23, Uppsala University, Department of Economics.
    13. Ji, Qiang & Liu, Bing-Yue & Fan, Ying, 2019. "Risk dependence of CoVaR and structural change between oil prices and exchange rates: A time-varying copula model," Energy Economics, Elsevier, vol. 77(C), pages 80-92.
    14. Zheng, Biao & Zhang, Yuquan W. & Qu, Fang & Geng, Yong & Yu, Haishan, 2022. "Do rare earths drive volatility spillover in crude oil, renewable energy, and high-technology markets? — A wavelet-based BEKK- GARCH-X approach," Energy, Elsevier, vol. 251(C).
    15. Lundgren, Amanda Ivarsson & Milicevic, Adriana & Uddin, Gazi Salah & Kang, Sang Hoon, 2018. "Connectedness network and dependence structure mechanism in green investments," Energy Economics, Elsevier, vol. 72(C), pages 145-153.
    16. Umar, Zaghum & Kenourgios, Dimitris & Papathanasiou, Sypros, 2020. "The static and dynamic connectedness of environmental, social, and governance investments: International evidence," Economic Modelling, Elsevier, vol. 93(C), pages 112-124.
    17. Dave Berger, 2022. "Investor sentiment: a retail trader activity approach," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 21(2), pages 61-82, April.
    18. Yao, Can-Zhong & Mo, Yi-Na & Zhang, Ze-Kun, 2021. "A study of the efficiency of the Chinese clean energy stock market and its correlation with the crude oil market based on an asymmetric multifractal scaling behavior analysis," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    19. Shang, Juan & Wang, Zhuo & Li, Ling & Chen, Yong & Li, Pengfei, 2018. "A study on the correlation between technology innovation and the new-type urbanization in Shaanxi province," Technological Forecasting and Social Change, Elsevier, vol. 135(C), pages 266-273.
    20. Niu, Hongli, 2021. "Correlations between crude oil and stocks prices of renewable energy and technology companies: A multiscale time-dependent analysis," Energy, Elsevier, vol. 221(C).
    21. Filis, George & Degiannakis, Stavros & Floros, Christos, 2011. "Dynamic correlation between stock market and oil prices: The case of oil-importing and oil-exporting countries," International Review of Financial Analysis, Elsevier, vol. 20(3), pages 152-164, June.
    22. Sadorsky, Perry, 1999. "Oil price shocks and stock market activity," Energy Economics, Elsevier, vol. 21(5), pages 449-469, October.
    23. Dastgir, Shabbir & Demir, Ender & Downing, Gareth & Gozgor, Giray & Lau, Chi Keung Marco, 2019. "The causal relationship between Bitcoin attention and Bitcoin returns: Evidence from the Copula-based Granger causality test," Finance Research Letters, Elsevier, vol. 28(C), pages 160-164.
    24. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    25. Gregor Dorfleitner & Johannes Grebler, 2022. "Corporate social responsibility and systematic risk: international evidence," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 23(1), pages 85-120, January.
    26. Manish Bansal & Vivek Kumar, 2021. "Forcing responsibility? Examining earnings management induced by mandatory corporate social responsibility: evidence from India," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 20(2), pages 194-216, August.
    27. Manish Bansal & Vivek Kumar, 2021. "Forcing responsibility? Examining earnings management induced by mandatory corporate social responsibility: evidence from India," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 20(2), pages 194-216, August.
    28. Canh, Nguyen Phuc & Wongchoti, Udomsak & Thanh, Su Dinh & Thong, Nguyen Trung, 2019. "Systematic risk in cryptocurrency market: Evidence from DCC-MGARCH model," Finance Research Letters, Elsevier, vol. 29(C), pages 90-100.
    29. Cong, Rong-Gang & Wei, Yi-Ming & Jiao, Jian-Lin & Fan, Ying, 2008. "Relationships between oil price shocks and stock market: An empirical analysis from China," Energy Policy, Elsevier, vol. 36(9), pages 3544-3553, September.
    30. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2019. "Range-based DCC models for covariance and value-at-risk forecasting," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 58-76.
    31. Akkoc, Ugur & Civcir, Irfan, 2019. "Dynamic linkages between strategic commodities and stock market in Turkey: Evidence from SVAR-DCC-GARCH model," Resources Policy, Elsevier, vol. 62(C), pages 231-239.
    32. Ahmad, Wasim, 2017. "On the dynamic dependence and investment performance of crude oil and clean energy stocks," Research in International Business and Finance, Elsevier, vol. 42(C), pages 376-389.
    33. Shah, Adil Ahmad & Paul, Manas & Bhanja, Niyati & Dar, Arif Billah, 2021. "Dynamics of connectedness across crude oil, precious metals and exchange rate: Evidence from time and frequency domains," Resources Policy, Elsevier, vol. 73(C).
    34. Sadorsky, Perry, 2012. "Correlations and volatility spillovers between oil prices and the stock prices of clean energy and technology companies," Energy Economics, Elsevier, vol. 34(1), pages 248-255.
    35. Broadstock, David C. & Cao, Hong & Zhang, Dayong, 2012. "Oil shocks and their impact on energy related stocks in China," Energy Economics, Elsevier, vol. 34(6), pages 1888-1895.
    36. Ji, Qiang & Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Risk spillover between energy and agricultural commodity markets: A dependence-switching CoVaR-copula model," Energy Economics, Elsevier, vol. 75(C), pages 14-27.
    37. Dave Berger, 2022. "Investor sentiment: a retail trader activity approach," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 21(2), pages 61-82, April.
    38. Li, Xiafei & Li, Bo & Wei, Guiwu & Bai, Lan & Wei, Yu & Liang, Chao, 2021. "Return connectedness among commodity and financial assets during the COVID-19 pandemic: Evidence from China and the US," Resources Policy, Elsevier, vol. 73(C).
    39. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2020. "Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions," JRFM, MDPI, vol. 13(4), pages 1-23, April.
    40. Gabauer, David & Gupta, Rangan, 2018. "On the transmission mechanism of country-specific and international economic uncertainty spillovers: Evidence from a TVP-VAR connectedness decomposition approach," Economics Letters, Elsevier, vol. 171(C), pages 63-71.
    41. Yilanci, Veli & Kilci, Esra N., 2021. "The role of economic policy uncertainty and geopolitical risk in predicting prices of precious metals: Evidence from a time-varying bootstrap causality test," Resources Policy, Elsevier, vol. 72(C).
    42. BenSaïda, Ahmed, 2019. "Good and bad volatility spillovers: An asymmetric connectedness," Journal of Financial Markets, Elsevier, vol. 43(C), pages 78-95.
    43. Li, Xiafei & Wei, Yu, 2018. "The dependence and risk spillover between crude oil market and China stock market: New evidence from a variational mode decomposition-based copula method," Energy Economics, Elsevier, vol. 74(C), pages 565-581.
    44. Naeem, Muhammad Abubakr & Balli, Faruk & Shahzad, Syed Jawad Hussain & de Bruin, Anne, 2020. "Energy commodity uncertainties and the systematic risk of US industries," Energy Economics, Elsevier, vol. 85(C).
    45. Rahman, Mohammad Mafizur, 2021. "The dynamic nexus of energy consumption, international trade and economic growth in BRICS and ASEAN countries: A panel causality test," Energy, Elsevier, vol. 229(C).
    46. Abdelmajid Hmaittane & Kais Bouslah & Bouchra M’Zali, 2019. "Does corporate social responsibility affect the cost of equity in controversial industry sectors?," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 18(4), pages 635-662, July.
    47. Mensi, Walid & Boubaker, Ferihane Zaraa & Al-Yahyaee, Khamis Hamed & Kang, Sang Hoon, 2018. "Dynamic volatility spillovers and connectedness between global, regional, and GIPSI stock markets," Finance Research Letters, Elsevier, vol. 25(C), pages 230-238.
    48. Shokoohi, Zeinab & Saghaian, Sayed, 2022. "Nexus of energy and food nutrition prices in oil importing and exporting countries: A panel VAR model," Energy, Elsevier, vol. 255(C).
    49. Zhang, Dayong, 2017. "Oil shocks and stock markets revisited: Measuring connectedness from a global perspective," Energy Economics, Elsevier, vol. 62(C), pages 323-333.
    50. Wen, Xiaoqian & Guo, Yanfeng & Wei, Yu & Huang, Dengshi, 2014. "How do the stock prices of new energy and fossil fuel companies correlate? Evidence from China," Energy Economics, Elsevier, vol. 41(C), pages 63-75.
    51. Ferrer, Román & Shahzad, Syed Jawad Hussain & López, Raquel & Jareño, Francisco, 2018. "Time and frequency dynamics of connectedness between renewable energy stocks and crude oil prices," Energy Economics, Elsevier, vol. 76(C), pages 1-20.
    52. Xi Zhang & Xu Wu & Linlin Zhang & Zhonglu Chen, 2022. "The Evaluation of Mean-Detrended Cross-Correlation Analysis Portfolio Strategy for Multiple risk Assets," Evaluation Review, , vol. 46(2), pages 138-164, April.
    53. Bondia, Ripsy & Ghosh, Sajal & Kanjilal, Kakali, 2016. "International crude oil prices and the stock prices of clean energy and technology companies: Evidence from non-linear cointegration tests with unknown structural breaks," Energy, Elsevier, vol. 101(C), pages 558-565.
    54. Ji, Qiang & Bouri, Elie & Lau, Chi Keung Marco & Roubaud, David, 2019. "Dynamic connectedness and integration in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 257-272.
    55. Dawar, Ishaan & Dutta, Anupam & Bouri, Elie & Saeed, Tareq, 2021. "Crude oil prices and clean energy stock indices: Lagged and asymmetric effects with quantile regression," Renewable Energy, Elsevier, vol. 163(C), pages 288-299.
    56. Liang, Chao & Umar, Muhammad & Ma, Feng & Huynh, Toan L.D., 2022. "Climate policy uncertainty and world renewable energy index volatility forecasting," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    57. Umar, Zaghum & Jareño, Francisco & Escribano, Ana, 2021. "Agricultural commodity markets and oil prices: An analysis of the dynamic return and volatility connectedness," Resources Policy, Elsevier, vol. 73(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wang, Fanyi & Ma, Wanying & Mirza, Nawazish & Altuntaş, Mehmet, 2023. "Green financing, financial uncertainty, geopolitical risk, and oil prices volatility," Resources Policy, Elsevier, vol. 83(C).
    2. Liu, Chen & Shao, Zhen & Jiao, Jianling & Yang, Shanlin, 2024. "How connected is withholding capacity to electricity, fossil fuel and carbon markets? Perspectives from a high renewable energy consumption economy," Energy Policy, Elsevier, vol. 185(C).
    3. Long, Houyin & Huang, Xiang & Wang, Jiaxin, 2023. "How does energy finance promote energy transition? Evidence from Shanghai crude oil futures," International Review of Financial Analysis, Elsevier, vol. 90(C).
    4. Yin, Libo & Cao, Hong & Guo, Yumei, 2024. "The information content of Shanghai crude oil futures vs WTI benchmark: Evidence from temporal and spatial dimensions," Energy Economics, Elsevier, vol. 132(C).
    5. Lei, Heng & Xue, Minggao & Ye, Jing, 2024. "The nexus between ReFi, carbon, fossil energy, and clean energy assets: Quantile time–frequency connectedness and portfolio implications," Energy Economics, Elsevier, vol. 132(C).
    6. Lang, Chunlin & Hu, Yang & Corbet, Shaen & Hou, Yang (Greg), 2024. "Tail risk connectedness in G7 stock markets: Understanding the impact of COVID-19 and related variants," Journal of Behavioral and Experimental Finance, Elsevier, vol. 41(C).
    7. Dai, Siwei & Du, Xiaoyan, 2023. "Discovering the role of trade diversification, natural resources, and environmental policy stringency on ecological sustainability in the BRICST region," Resources Policy, Elsevier, vol. 85(PB).
    8. Dai, Yun-Shi & Dai, Peng-Fei & Zhou, Wei-Xing, 2023. "Tail dependence structure and extreme risk spillover effects between the international agricultural futures and spot markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    9. Lu, Xunfa & Huang, Nan & Mo, Jianlei, 2024. "Time-varying causalities from the COVID-19 media coverage to the dynamic spillovers among the cryptocurrency, the clean energy, and the crude oil," Energy Economics, Elsevier, vol. 132(C).
    10. Naeem, Muhammad Abubakr & Hamouda, Foued & Karim, Sitara, 2024. "Tail risk spillover effects in commodity markets: A comparative study of crisis periods," Journal of Commodity Markets, Elsevier, vol. 33(C).
    11. Fang, Shuya & Fang, Wei, 2023. "How fiscal decentralization and trade diversification influence sustainable development: Moderating role of resources dependency," Resources Policy, Elsevier, vol. 84(C).
    12. Yang, Bin & Wu, Qiong & Sharif, Arshian & Uddin, Gazi Salah, 2023. "Non-linear impact of natural resources, green financing, and energy transition on sustainable environment: A way out for common prosperity in NORDIC countries," Resources Policy, Elsevier, vol. 83(C).
    13. Li, Houjian & Huang, Xinya & Guo, Lili, 2023. "Extreme risk dependence and time-varying spillover between crude oil, commodity market and inflation in China," Energy Economics, Elsevier, vol. 127(PB).
    14. Zhang, Jiaming & Guo, Songlin & Dou, Bin & Xie, Bingyuan, 2023. "Evidence of the internationalization of China's crude oil futures: Asymmetric linkages to global financial risks," Energy Economics, Elsevier, vol. 127(PA).
    15. Li, Xin & Umar, Muhammad & Zhu, Cun-Bin & Oprean-Stan, Camelia, 2023. "Can geopolitical risk stably predict crude oil prices? A multi-dimensional perspective," Resources Policy, Elsevier, vol. 85(PA).
    16. Xiao, Xunyong & Li, Aixi & Kchouri, Bilal & Shan, Shan, 2024. "Tracing the dynamic impact of energy transitions on equity market volatility in an era of financial turbulence," Energy Economics, Elsevier, vol. 133(C).
    17. Su, Chi-Wei & Wang, Dan & Mirza, Nawazish & Zhong, Yifan & Umar, Muhammad, 2023. "The impact of consumer confidence on oil prices," Energy Economics, Elsevier, vol. 124(C).
    18. Zhang, Dongyang & Wang, Cao & Wang, Yizhi, 2024. "Unveiling the critical nexus: Volatility of crude oil future prices and trade partner’s cash holding behavior in the face of the Russia–Ukraine conflict," Energy Economics, Elsevier, vol. 132(C).
    19. Khan, Faridoon & Muhammadullah, Sara & Sharif, Arshian & Lee, Chien-Chiang, 2024. "The role of green energy stock market in forecasting China's crude oil market: An application of IIS approach and sparse regression models," Energy Economics, Elsevier, vol. 130(C).
    20. Safi, Adnan & Wei, Xin & Sansaloni, Eduard Montesinos & Umar, Muhammad, 2023. "Breaking down the complexity of sustainable development: A focus on resources, economic complexity, and innovation," Resources Policy, Elsevier, vol. 83(C).
    21. Luo, Changqing & Qu, Yi & Su, Yaya & Dong, Liang, 2024. "Risk spillover from international crude oil markets to China’s financial markets: Evidence from extreme events and U.S. monetary policy," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dai, Zhifeng & Luo, Zhuang & Liu, Chang, 2023. "Dynamic volatility spillovers and investment strategies between crude oil, new energy, and resource related sectors," Resources Policy, Elsevier, vol. 83(C).
    2. Ghaemi Asl, Mahdi & Adekoya, Oluwasegun Babatunde & Rashidi, Muhammad Mahdi & Ghasemi Doudkanlou, Mohammad & Dolatabadi, Ali, 2022. "Forecast of Bayesian-based dynamic connectedness between oil market and Islamic stock indices of Islamic oil-exporting countries: Application of the cascade-forward backpropagation network," Resources Policy, Elsevier, vol. 77(C).
    3. Wei, Yu & Zhang, Jiahao & Bai, Lan & Wang, Yizhi, 2023. "Connectedness among El Niño-Southern Oscillation, carbon emission allowance, crude oil and renewable energy stock markets: Time- and frequency-domain evidence based on TVP-VAR model," Renewable Energy, Elsevier, vol. 202(C), pages 289-309.
    4. Luo, Keyu & Guo, Qiang & Li, Xiafei, 2022. "Can the return connectedness indices from grey energy to natural gas help to forecast the natural gas returns?," Energy Economics, Elsevier, vol. 109(C).
    5. Dai, Zhifeng & Zhu, Haoyang & Zhang, Xinhua, 2022. "Dynamic spillover effects and portfolio strategies between crude oil, gold and Chinese stock markets related to new energy vehicle," Energy Economics, Elsevier, vol. 109(C).
    6. Liu, Zhenhua & Shi, Xunpeng & Zhai, Pengxiang & Wu, Shan & Ding, Zhihua & Zhou, Yuqin, 2021. "Tail risk connectedness in the oil-stock nexus: Evidence from a novel quantile spillover approach," Resources Policy, Elsevier, vol. 74(C).
    7. Umar, Muhammad & Farid, Saqib & Naeem, Muhammad Abubakr, 2022. "Time-frequency connectedness among clean-energy stocks and fossil fuel markets: Comparison between financial, oil and pandemic crisis," Energy, Elsevier, vol. 240(C).
    8. Yufeng Chen & Wenqi Li & Xi Jin, 2018. "Volatility Spillovers between Crude Oil Prices and New Energy Stock Price in China," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 43-62, December.
    9. Tan, Xueping & Geng, Yong & Vivian, Andrew & Wang, Xinyu, 2021. "Measuring risk spillovers between oil and clean energy stocks: Evidence from a systematic framework," Resources Policy, Elsevier, vol. 74(C).
    10. Li, Xiafei & Li, Bo & Wei, Guiwu & Bai, Lan & Wei, Yu & Liang, Chao, 2021. "Return connectedness among commodity and financial assets during the COVID-19 pandemic: Evidence from China and the US," Resources Policy, Elsevier, vol. 73(C).
    11. Evrim Mandacı, Pınar & Cagli, Efe Çaglar & Taşkın, Dilvin, 2020. "Dynamic connectedness and portfolio strategies: Energy and metal markets," Resources Policy, Elsevier, vol. 68(C).
    12. Wang, Zi-Xin & Liu, Bing-Yue & Fan, Ying, 2023. "Network connectedness between China's crude oil futures and sector stock indices," Energy Economics, Elsevier, vol. 125(C).
    13. Mensi, Walid & Al Rababa'a, Abdel Razzaq & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Asymmetric spillover and network connectedness between crude oil, gold, and Chinese sector stock markets," Energy Economics, Elsevier, vol. 98(C).
    14. Tiwari, Aviral Kumar & Aikins Abakah, Emmanuel Joel & Doğan, Buhari & Adekoya, Oluwasegun B. & Wohar, Mark, 2024. "Asymmetric spillover effects in energy markets," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 470-502.
    15. Liang, Chao & Goodell, John W. & Li, Xiafei, 2024. "Impacts of carbon market and climate policy uncertainties on financial and economic stability: Evidence from connectedness network analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 92(C).
    16. Elsayed, Ahmed H. & Nasreen, Samia & Tiwari, Aviral Kumar, 2020. "Time-varying co-movements between energy market and global financial markets: Implication for portfolio diversification and hedging strategies," Energy Economics, Elsevier, vol. 90(C).
    17. Capucine Nobletz, 2021. "Return spillovers between green energy indexes and financial markets: a first sectoral approach," EconomiX Working Papers 2021-24, University of Paris Nanterre, EconomiX.
    18. Urom, Christian & Mzoughi, Hela & Ndubuisi, Gideon & Guesmi, Khaled, 2022. "Directional predictability and time-frequency spillovers among clean energy sectors and oil price uncertainty," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 326-341.
    19. Iqbal, Najaf & Naeem, Muhammad Abubakr & Suleman, Muhammed Tahir, 2022. "Quantifying the asymmetric spillovers in sustainable investments," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    20. Çevik, Emre & Çevik, Emrah İsmail & Dibooglu, Sel & Cergibozan, Raif & Bugan, Mehmet Fatih & Destek, Mehmet Akif, 2022. "Connectedness and risk spillovers between crude oil and clean energy stock markets," MPRA Paper 117558, University Library of Munich, Germany.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:119:y:2023:i:c:s014098832300066x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.