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Nonparametric modeling of carbon prices

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  1. Zhu, Bangzhu & Ma, Shujiao & Chevallier, Julien & Wei, Yiming, 2014. "Modelling the dynamics of European carbon futures price: A Zipf analysis," Economic Modelling, Elsevier, vol. 38(C), pages 372-380.
  2. Song, Yazhi & Liu, Tiansen & Liang, Dapeng & Li, Yin & Song, Xiaoqiu, 2019. "A Fuzzy Stochastic Model for Carbon Price Prediction Under the Effect of Demand-related Policy in China's Carbon Market," Ecological Economics, Elsevier, vol. 157(C), pages 253-265.
  3. Byun, Suk Joon & Cho, Hangjun, 2013. "Forecasting carbon futures volatility using GARCH models with energy volatilities," Energy Economics, Elsevier, vol. 40(C), pages 207-221.
  4. 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.
  5. Chai, Shanglei & Yang, Xiaoli & Zhang, Zhen & Abedin, Mohammad Zoynul & Lucey, Brian, 2022. "Regional imbalances of market efficiency in China’s pilot emission trading schemes (ETS): A multifractal perspective," Research in International Business and Finance, Elsevier, vol. 63(C).
  6. 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.
  7. Tol, Richard S.J., 2012. "A cost–benefit analysis of the EU 20/20/2020 package," Energy Policy, Elsevier, vol. 49(C), pages 288-295.
  8. 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.
  9. Zachmann, Georg, 2013. "A stochastic fuel switching model for electricity prices," Energy Economics, Elsevier, vol. 35(C), pages 5-13.
  10. Jujie Wang & Zhenzhen Zhuang, 2023. "A novel cluster based multi-index nonlinear ensemble framework for carbon price forecasting," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 6225-6247, July.
  11. Feng, Ling & Wang, Jieyu, 2023. "Random sources correlations and carbon futures pricing," International Review of Financial Analysis, Elsevier, vol. 86(C).
  12. Xu, Hua & Wang, Minggang & Jiang, Shumin & Yang, Weiguo, 2020. "Carbon price forecasting with complex network and extreme learning machine," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
  13. 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).
  14. Kaijian He & Qian Yang & Lei Ji & Jingcheng Pan & Yingchao Zou, 2023. "Financial Time Series Forecasting with the Deep Learning Ensemble Model," Mathematics, MDPI, vol. 11(4), pages 1-15, February.
  15. Yan, Kai & Zhang, Wei & Shen, Dehua, 2020. "Stylized facts of the carbon emission market in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
  16. Bangzhu Zhu & Jingyi Zhang & Chunzhuo Wan & Julien Chevallier & Ping Wang, 2023. "An evolutionary cost‐sensitive support vector machine for carbon price trend forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 741-755, July.
  17. 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.
  18. 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.
  19. Ren, Xiaohang & Duan, Kun & Tao, Lizhu & Shi, Yukun & Yan, Cheng, 2022. "Carbon prices forecasting in quantiles," Energy Economics, Elsevier, vol. 108(C).
  20. 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.
  21. Hyeonho Kim & Yujin Kim & Yongho Ko & Seungwoo Han, 2022. "Performance Comparison of Predictive Methodologies for Carbon Emission Credit Price in the Korea Emission Trading System," Sustainability, MDPI, vol. 14(13), pages 1-20, July.
  22. 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).
  23. 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.
  24. 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).
  25. Yue-Jun Zhang, 2016. "Research on carbon emission trading mechanisms: current status and future possibilities," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 39(1/2), pages 89-107.
  26. 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.
  27. Zhu, Bangzhu & Han, Dong & Wang, Ping & Wu, Zhanchi & Zhang, Tao & Wei, Yi-Ming, 2017. "Forecasting carbon price using empirical mode decomposition and evolutionary least squares support vector regression," Applied Energy, Elsevier, vol. 191(C), pages 521-530.
  28. 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.
  29. 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.
  30. 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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