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Forecasting carbon futures volatility using GARCH models with energy volatilities

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Cited by:

  1. Cristiano Salvagnin, 2024. "Evolving Dynamics: Bibliometric Insights into the Economics of the EU ETS Market," Papers 2409.01739, arXiv.org, revised Oct 2024.
  2. Federico Galán-Valdivieso & Elena Villar-Rubio & María-Dolores Huete-Morales, 2018. "The erratic behaviour of the EU ETS on the path towards consolidation and price stability," International Environmental Agreements: Politics, Law and Economics, Springer, vol. 18(5), pages 689-706, October.
  3. Ding, Lili & Zhang, Rui & Zhao, Xin, 2024. "Forecasting carbon price in China unified carbon market using a novel hybrid method with three-stage algorithm and long short-term memory neural networks," Energy, Elsevier, vol. 288(C).
  4. Gao, Feng & Shao, Xueyan, 2022. "A novel interval decomposition ensemble model for interval carbon price forecasting," Energy, Elsevier, vol. 243(C).
  5. Xinyu Wu & Xuebao Yin & Xueting Mei, 2022. "Forecasting the Volatility of European Union Allowance Futures with Climate Policy Uncertainty Using the EGARCH-MIDAS Model," Sustainability, MDPI, vol. 14(7), pages 1-13, April.
  6. Li, Gang & Li, Yong, 2015. "Forecasting copper futures volatility under model uncertainty," Resources Policy, Elsevier, vol. 46(P2), pages 167-176.
  7. Xiaohua Song & Wen Zhang & Zeqi Ge & Siqi Huang & Yamin Huang & Sijia Xiong, 2022. "A Study of the Influencing Factors on the Carbon Emission Trading Price in China Based on the Improved Gray Relational Analysis Model," Sustainability, MDPI, vol. 14(13), pages 1-27, June.
  8. Huang, Wenyang & Zhao, Jianyu & Wang, Xiaokang, 2024. "Model-driven multimodal LSTM-CNN for unbiased structural forecasting of European Union allowances open-high-low-close price," Energy Economics, Elsevier, vol. 132(C).
  9. Katarzyna Rudnik & Anna Hnydiuk-Stefan & Aneta Kucińska-Landwójtowicz & Łukasz Mach, 2022. "Forecasting Day-Ahead Carbon Price by Modelling Its Determinants Using the PCA-Based Approach," Energies, MDPI, vol. 15(21), pages 1-23, October.
  10. Qiao, Sen & Dang, Yi Jing & Ren, Zheng Yu & Zhang, Kai Quan, 2023. "The dynamic spillovers among carbon, fossil energy and electricity markets based on a TVP-VAR-SV method," Energy, Elsevier, vol. 266(C).
  11. Guo, Xiaozhu & Huang, Dengshi & Li, Xiafei & Liang, Chao, 2023. "Are categorical EPU indices predictable for carbon futures volatility? Evidence from the machine learning method," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 672-693.
  12. Zhikai Zhang & Yaojie Zhang & Yudong Wang & Qunwei Wang, 2024. "The predictability of carbon futures volatility: New evidence from the spillovers of fossil energy futures returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(4), pages 557-584, April.
  13. Liu, Tao & Guan, Xinyue & Wei, Yigang & Xue, Shan & Xu, Liang, 2023. "Impact of economic policy uncertainty on the volatility of China's emission trading scheme pilots," Energy Economics, Elsevier, vol. 121(C).
  14. Zhu, Jiaming & Wu, Peng & Chen, Huayou & Liu, Jinpei & Zhou, Ligang, 2019. "Carbon price forecasting with variational mode decomposition and optimal combined model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 140-158.
  15. Yaqi Wu & Chen Zhang & Po Yun & Dandan Zhu & Wei Cao & Zulfiqar Ali Wagan, 2021. "Time–frequency analysis of the interaction mechanism between European carbon and crude oil markets," Energy & Environment, , vol. 32(7), pages 1331-1357, November.
  16. Liu, Jianing & Man, Yuanyuan & Dong, Xiuliang, 2023. "Tail dependence and risk spillover effects between China's carbon market and energy markets," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 553-567.
  17. Rita Sousa & Luís Aguiar-Conraria & Maria Joana Soares, 2014. "Carbon Financial Markets: a time-frequency analysis of CO2 price drivers," NIPE Working Papers 03/2014, NIPE - Universidade do Minho.
  18. Zhao, Xin & Han, Meng & Ding, Lili & Kang, Wanglin, 2018. "Usefulness of economic and energy data at different frequencies for carbon price forecasting in the EU ETS," Applied Energy, Elsevier, vol. 216(C), pages 132-141.
  19. Adekoya, Oluwasegun B. & Oliyide, Johnson A. & Noman, Ambreen, 2021. "The volatility connectedness of the EU carbon market with commodity and financial markets in time- and frequency-domain: The role of the U.S. economic policy uncertainty," Resources Policy, Elsevier, vol. 74(C).
  20. Po Yun & Chen Zhang & Yaqi Wu & Xianzi Yang & Zulfiqar Ali Wagan, 2020. "A Novel Extended Higher-Order Moment Multi-Factor Framework for Forecasting the Carbon Price: Testing on the Multilayer Long Short-Term Memory Network," Sustainability, MDPI, vol. 12(5), pages 1-16, March.
  21. Nikitopoulos, Christina Sklibosios & Thomas, Alice Carole & Wang, Jianxin, 2023. "The economic impact of daily volatility persistence on energy markets," Journal of Commodity Markets, Elsevier, vol. 30(C).
  22. Wang, Lu & Ma, Feng & Liu, Jing & Yang, Lin, 2020. "Forecasting stock price volatility: New evidence from the GARCH-MIDAS model," International Journal of Forecasting, Elsevier, vol. 36(2), pages 684-694.
  23. Xian, Sidong & Feng, Miaomiao & Cheng, Yue, 2023. "Incremental nonlinear trend fuzzy granulation for carbon trading time series forecast," Applied Energy, Elsevier, vol. 352(C).
  24. repec:hum:wpaper:sfb649dp2015-026 is not listed on IDEAS
  25. Huawei Niu & Tianyu Liu, 2024. "Forecasting the volatility of European Union allowance futures with macroeconomic variables using the GJR-GARCH-MIDAS model," Empirical Economics, Springer, vol. 67(1), pages 75-96, July.
  26. Wang, Xiong & Li, Jingyao & Ren, Xiaohang & Bu, Ruijun & Jawadi, Fredj, 2023. "Economic policy uncertainty and dynamic correlations in energy markets: Assessment and solutions," Energy Economics, Elsevier, vol. 117(C).
  27. Jiang, Wei & Chen, Yunfei, 2022. "The time-frequency connectedness among carbon, traditional/new energy and material markets of China in pre- and post-COVID-19 outbreak periods," Energy, Elsevier, vol. 246(C).
  28. Tang, Chun & Liu, Xiaoxing & Chen, Guangkun, 2023. "The spillover effects in the “Energy – Carbon – Stock” system – Evidence from China," Energy, Elsevier, vol. 278(PA).
  29. Zhang, Chen & Yun, Po & Wagan, Zulfiqar Ali, 2019. "Study on the wandering weekday effect of the international carbon market based on trend moderation effect," Finance Research Letters, Elsevier, vol. 28(C), pages 319-327.
  30. Jia, Rui-Lin & Wang, Dong-Hua & Tu, Jing-Qing & Li, Sai-Ping, 2016. "Correlation between agricultural markets in dynamic perspective—Evidence from China and the US futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 464(C), pages 83-92.
  31. Bangzhu Zhu & Xuetao Shi & Julien Chevallier & Ping Wang & Yi‐Ming Wei, 2016. "An Adaptive Multiscale Ensemble Learning Paradigm for Nonstationary and Nonlinear Energy Price Time Series Forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(7), pages 633-651, November.
  32. Wang, Jiqian & Guo, Xiaozhu & Tan, Xueping & Chevallier, Julien & Ma, Feng, 2023. "Which exogenous driver is informative in forecasting European carbon volatility: Bond, commodity, stock or uncertainty?," Energy Economics, Elsevier, vol. 117(C).
  33. Yumin Li & Ruiqi Yang & Xiaoman Wang & Jiaming Zhu & Nan Song, 2023. "Carbon Price Combination Forecasting Model Based on Lasso Regression and Optimal Integration," Sustainability, MDPI, vol. 15(12), pages 1-26, June.
  34. Demiralay, Sercan & Gencer, Hatice Gaye & Bayraci, Selcuk, 2022. "Carbon credit futures as an emerging asset: Hedging, diversification and downside risks," Energy Economics, Elsevier, vol. 113(C).
  35. Wei Sun & Ming Duan, 2019. "Analysis and Forecasting of the Carbon Price in China’s Regional Carbon Markets Based on Fast Ensemble Empirical Mode Decomposition, Phase Space Reconstruction, and an Improved Extreme Learning Machin," Energies, MDPI, vol. 12(2), pages 1-27, January.
  36. Xu, Yifan & Che, Jinxing & Xia, Wenxin & Hu, Kun & Jiang, Weirui, 2024. "A novel paradigm: Addressing real-time decomposition challenges in carbon price prediction," Applied Energy, Elsevier, vol. 364(C).
  37. Xiaohang Ren & Kang Yuan & Lizhu Tao & Cheng Yan, 2024. "Carbon Prices Forecasting Using Group Information," Energy RESEARCH LETTERS, Asia-Pacific Applied Economics Association, vol. 4(4), pages 1-6.
  38. Shen, Zhiwei & Ritter, Matthias, 2015. "Forecasting volatility of wind power production," SFB 649 Discussion Papers 2015-026, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  39. Qi, Shaozhou & Cheng, Shihan & Tan, Xiujie & Feng, Shenghao & Zhou, Qi, 2022. "Predicting China's carbon price based on a multi-scale integrated model," Applied Energy, Elsevier, vol. 324(C).
  40. Quande Qin & Huangda He & Li Li & Ling-Yun He, 2020. "A Novel Decomposition-Ensemble Based Carbon Price Forecasting Model Integrated with Local Polynomial Prediction," Computational Economics, Springer;Society for Computational Economics, vol. 55(4), pages 1249-1273, April.
  41. Zouheir Mighri & Raouf Jaziri, 2023. "Long-Memory, Asymmetry and Fat-Tailed GARCH Models in Value-at-Risk Estimation: Empirical Evidence from the Global Real Estate Markets," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(1), pages 41-97, March.
  42. Jian Liu & Ziting Zhang & Lizhao Yan & Fenghua Wen, 2021. "Forecasting the volatility of EUA futures with economic policy uncertainty using the GARCH-MIDAS model," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-19, December.
  43. Shuhua Chang & Xinyu Wang, 2015. "Modelling and Computation in the Valuation of Carbon Derivatives with Stochastic Convenience Yields," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-35, May.
  44. Xu Gong & Boqiang Lin, 2021. "Effects of structural changes on the prediction of downside volatility in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(7), pages 1124-1153, July.
  45. Qin, Chaoyong & Qin, Dongling & Jiang, Qiuxian & Zhu, Bangzhu, 2024. "Forecasting carbon price with attention mechanism and bidirectional long short-term memory network," Energy, Elsevier, vol. 299(C).
  46. Bangzhu Zhu & Shunxin Ye & Ping Wang & Julien Chevallier & Yi‐Ming Wei, 2022. "Forecasting carbon price using a multi‐objective least squares support vector machine with mixture kernels," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 100-117, January.
  47. Rita Sousa & Luís Francisco Aguiar-Conraria & Maria Joana Soares, 2014. "Carbon and Energy Prices: Surfing the Wavelets of California," NIPE Working Papers 19/2014, NIPE - Universidade do Minho.
  48. Zhu, Bangzhu & Ye, Shunxin & Wang, Ping & He, Kaijian & Zhang, Tao & Wei, Yi-Ming, 2018. "A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting," Energy Economics, Elsevier, vol. 70(C), pages 143-157.
  49. Jin, Jiayu & Han, Liyan & Wu, Lei & Zeng, Hongchao, 2020. "The hedging effect of green bonds on carbon market risk," International Review of Financial Analysis, Elsevier, vol. 71(C).
  50. Yongmei Fang & Bo Guan & Shangjuan Wu & Saeed Heravi, 2020. "Optimal forecast combination based on ensemble empirical mode decomposition for agricultural commodity futures prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 877-886, September.
  51. Huang, Zhehao & Dong, Hao & Jia, Shuaishuai, 2022. "Equilibrium pricing for carbon emission in response to the target of carbon emission peaking," Energy Economics, Elsevier, vol. 112(C).
  52. Cristiano Salvagnin & Aldo Glielmo & Maria Elena De Giuli & Antonietta Mira, 2024. "Investigating the price determinants of the European Emission Trading System: a non-parametric approach," Papers 2406.05094, arXiv.org.
  53. Jianguo Zhou & Dongfeng Chen, 2021. "Carbon Price Forecasting Based on Improved CEEMDAN and Extreme Learning Machine Optimized by Sparrow Search Algorithm," Sustainability, MDPI, vol. 13(9), pages 1-20, April.
  54. Ren, Xiaohang & Duan, Kun & Tao, Lizhu & Shi, Yukun & Yan, Cheng, 2022. "Carbon prices forecasting in quantiles," Energy Economics, Elsevier, vol. 108(C).
  55. Xing Zhang & Chongchong Zhang & Zhuoqun Wei, 2019. "Carbon Price Forecasting Based on Multi-Resolution Singular Value Decomposition and Extreme Learning Machine Optimized by the Moth–Flame Optimization Algorithm Considering Energy and Economic Factors," Energies, MDPI, vol. 12(22), pages 1-23, November.
  56. Palma, Alessia & Paltrinieri, Andrea & Goodell, John W. & Oriani, Marco Ercole, 2024. "The black box of natural gas market: Past, present, and future," International Review of Financial Analysis, Elsevier, vol. 94(C).
  57. Tang, Chun & Yang, Guangyi & Liu, Xiaoxing, 2024. "Risk spillover within the carbon-energy system – New evidence considering China's national carbon market," Economic Analysis and Policy, Elsevier, vol. 81(C), pages 1227-1240.
  58. Houjian Li & Xinya Huang & Deheng Zhou & Andi Cao & Mengying Su & Yufeng Wang & Lili Guo, 2022. "Forecasting Carbon Price in China: A Multimodel Comparison," IJERPH, MDPI, vol. 19(10), pages 1-16, May.
  59. Li, Ming-Jia & Song, Chen-Xi & Tao, Wen-Quan, 2016. "A hybrid model for explaining the short-term dynamics of energy efficiency of China’s thermal power plants," Applied Energy, Elsevier, vol. 169(C), pages 738-747.
  60. Wang, Piao & Tao, Zhifu & Liu, Jinpei & Chen, Huayou, 2023. "Improving the forecasting accuracy of interval-valued carbon price from a novel multi-scale framework with outliers detection: An improved interval-valued time series analysis mode," Energy Economics, Elsevier, vol. 118(C).
  61. Shen, Zhiwei & Ritter, Matthias, 2016. "Forecasting volatility of wind power production," Applied Energy, Elsevier, vol. 176(C), pages 295-308.
  62. Peng Ye & Yong Li & Abu Bakkar Siddik, 2023. "Forecasting the Return of Carbon Price in the Chinese Market Based on an Improved Stacking Ensemble Algorithm," Energies, MDPI, vol. 16(11), pages 1-39, June.
  63. Peng Chen & Andrew Vivian & Cheng Ye, 2022. "Forecasting carbon futures price: a hybrid method incorporating fuzzy entropy and extreme learning machine," Annals of Operations Research, Springer, vol. 313(1), pages 559-601, June.
  64. Wang, Deyun & Luo, Hongyuan & Grunder, Olivier & Lin, Yanbing & Guo, Haixiang, 2017. "Multi-step ahead electricity price forecasting using a hybrid model based on two-layer decomposition technique and BP neural network optimized by firefly algorithm," Applied Energy, Elsevier, vol. 190(C), pages 390-407.
  65. Chen, Weidong & Xiong, Shi & Chen, Quanyu, 2022. "Characterizing the dynamic evolutionary behavior of multivariate price movement fluctuation in the carbon-fuel energy markets system from complex network perspective," Energy, Elsevier, vol. 239(PA).
  66. Zhu, Mengrui & Xu, Hua & Wang, Minggang & Tian, Lixin, 2024. "Carbon price interval prediction method based on probability density recurrence network and interval multi-layer perceptron," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 636(C).
  67. Gong, Xu & Shi, Rong & Xu, Jun & Lin, Boqiang, 2021. "Analyzing spillover effects between carbon and fossil energy markets from a time-varying perspective," Applied Energy, Elsevier, vol. 285(C).
  68. Wang, Jianzhou & Niu, Xinsong & Zhang, Linyue & Lv, Mengzheng, 2021. "Point and interval prediction for non-ferrous metals based on a hybrid prediction framework," Resources Policy, Elsevier, vol. 73(C).
  69. Chen, Linfei & Zhao, Xuefeng, 2024. "A multiscale and multivariable differentiated learning for carbon price forecasting," Energy Economics, Elsevier, vol. 131(C).
  70. Hartvig, Áron Dénes & Pap, Áron & Pálos, Péter, 2023. "EU Climate Change News Index: Forecasting EU ETS prices with online news," Finance Research Letters, Elsevier, vol. 54(C).
  71. Po Yun & Chen Zhang & Yaqi Wu & Yu Yang, 2022. "Forecasting Carbon Dioxide Price Using a Time-Varying High-Order Moment Hybrid Model of NAGARCHSK and Gated Recurrent Unit Network," IJERPH, MDPI, vol. 19(2), pages 1-19, January.
  72. Huang, Yumeng & Dai, Xingyu & Wang, Qunwei & Zhou, Dequn, 2021. "A hybrid model for carbon price forecastingusing GARCH and long short-term memory network," Applied Energy, Elsevier, vol. 285(C).
  73. Zhou, Feite & Huang, Zhehao & Zhang, Changhong, 2022. "Carbon price forecasting based on CEEMDAN and LSTM," Applied Energy, Elsevier, vol. 311(C).
  74. Yue Xu & Dayu Zhai, 2022. "Impact of Changes in Membership on Prices of a Unified Carbon Market: Case Study of the European Union Emissions Trading System," Sustainability, MDPI, vol. 14(21), pages 1-16, October.
  75. Wang, Yong & Liu, Shimiao & Abedin, Mohammad Zoynul & Lucey, Brian, 2024. "Volatility spillover and hedging strategies among Chinese carbon, energy, and electricity markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
  76. Jianguo Zhou & Shiguo Wang, 2021. "A Carbon Price Prediction Model Based on the Secondary Decomposition Algorithm and Influencing Factors," Energies, MDPI, vol. 14(5), pages 1-20, March.
  77. Jesús Molina‐Muñoz & Andrés Mora‐Valencia & Javier Perote, 2024. "Predicting carbon and oil price returns using hybrid models based on machine and deep learning," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 31(2), June.
  78. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2022. "Forecasting European carbon returns using dimension reduction techniques: Commodity versus financial fundamentals," International Journal of Forecasting, Elsevier, vol. 38(3), pages 944-969.
  79. Li, Jingmiao & Liu, Dehong, 2023. "Carbon price forecasting based on secondary decomposition and feature screening," Energy, Elsevier, vol. 278(PA).
  80. Jianguo Zhou & Xuejing Huo & Xiaolei Xu & Yushuo Li, 2019. "Forecasting the Carbon Price Using Extreme-Point Symmetric Mode Decomposition and Extreme Learning Machine Optimized by the Grey Wolf Optimizer Algorithm," Energies, MDPI, vol. 12(5), pages 1-22, March.
  81. Tan, Xue-Ping & Wang, Xin-Yu, 2017. "Dependence changes between the carbon price and its fundamentals: A quantile regression approach," Applied Energy, Elsevier, vol. 190(C), pages 306-325.
  82. Bekhzod Kuziboev & Petra Vysušilová & Raufhon Salahodjaev & Alibek Rajabov & Tukhtabek Rakhimov, 2023. "The Volatility Assessment of CO2 Emissions in Uzbekistan: ARCH/GARCH Models," International Journal of Energy Economics and Policy, Econjournals, vol. 13(5), pages 1-7, September.
  83. Sun, Wei & Zhang, Chongchong, 2018. "Analysis and forecasting of the carbon price using multi—resolution singular value decomposition and extreme learning machine optimized by adaptive whale optimization algorithm," Applied Energy, Elsevier, vol. 231(C), pages 1354-1371.
  84. Rita Sousa & Luís Aguiar-Conraria, 2014. "Dynamics of CO2 price drivers," NIPE Working Papers 02/2014, NIPE - Universidade do Minho.
  85. Getachew Nigatu, 2016. "Assessing the effects of climate change policy on the volatility of carbon prices in reference to the Great Recession," Journal of Environmental Economics and Policy, Taylor & Francis Journals, vol. 5(2), pages 200-215, July.
  86. Sousa, Rita & Aguiar-Conraria, Luís & Soares, Maria Joana, 2014. "Carbon financial markets: A time–frequency analysis of CO2 prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 118-127.
  87. Wang, Yudong & Guo, Zhuangyue, 2018. "The dynamic spillover between carbon and energy markets: New evidence," Energy, Elsevier, vol. 149(C), pages 24-33.
  88. Wen Zhang & Zhibin Wu, 2022. "Optimal hybrid framework for carbon price forecasting using time series analysis and least squares support vector machine," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 615-632, April.
  89. Wang, Minggang & Zhu, Mengrui & Tian, Lixin, 2022. "A novel framework for carbon price forecasting with uncertainties," Energy Economics, Elsevier, vol. 112(C).
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