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Interval-valued time series forecasting using a novel hybrid HoltI and MSVR model

Citations

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Cited by:

  1. Gao, Feng & Shao, Xueyan, 2022. "A novel interval decomposition ensemble model for interval carbon price forecasting," Energy, Elsevier, vol. 243(C).
  2. Rui Luo & Jinpei Liu & Piao Wang & Zhifu Tao & Huayou Chen, 2024. "A multisource data‐driven combined forecasting model based on internet search keyword screening method for interval soybean futures price," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 366-390, March.
  3. Bruck, Axel & Díaz Ruano, Santiago & Auer, Hans, 2022. "One piece of the puzzle towards 100 Positive Energy Districts (PEDs) across Europe by 2025: An open-source approach to unveil favourable locations of PV-based PEDs from a techno-economic perspective," Energy, Elsevier, vol. 254(PA).
  4. 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.
  5. Sun, Shaolong & Wang, Shouyang & Wei, Yunjie, 2019. "A new multiscale decomposition ensemble approach for forecasting exchange rates," Economic Modelling, Elsevier, vol. 81(C), pages 49-58.
  6. Sun, Yuying & Zhang, Xinyu & Wan, Alan T.K. & Wang, Shouyang, 2022. "Model averaging for interval-valued data," European Journal of Operational Research, Elsevier, vol. 301(2), pages 772-784.
  7. Sun, Shaolong & Sun, Yuying & Wang, Shouyang & Wei, Yunjie, 2018. "Interval decomposition ensemble approach for crude oil price forecasting," Energy Economics, Elsevier, vol. 76(C), pages 274-287.
  8. Piao Wang & Shahid Hussain Gurmani & Zhifu Tao & Jinpei Liu & Huayou Chen, 2024. "Interval time series forecasting: A systematic literature review," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 249-285, March.
  9. Liu, Shuihan & Wei, Yunjie & Peng, Pan & Wang, Shouyang, 2025. "Joint interval forecasting of renewable energy stocks using a secondary decomposition approach," Renewable Energy, Elsevier, vol. 245(C).
  10. Lei, Heng & Xue, Minggao & Liu, Huiling, 2022. "Probability distribution forecasting of carbon allowance prices: A hybrid model considering multiple influencing factors," Energy Economics, Elsevier, vol. 113(C).
  11. Souza, Waldemar & Palazzi, Rafeal & Campani, Carlos Heitor & Bohl, Martin, 2019. "Evaluation of Ambiguity in Commodity Futures Markets: Analysis of Corn and Coffee Futures Prices," 2019 Conference, April 15-16, 2019, Minneapolis, Minnesota 309636, NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
  12. OlaOluwa S. Yaya & Xuan Vinh Vo & Ahamuefula E. Ogbonna & Adeolu O. Adewuyi, 2022. "Modelling cryptocurrency high–low prices using fractional cointegrating VAR," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 489-505, January.
  13. Wenyang Huang & Huiwen Wang & Shanshan Wang, 2021. "Dimension reduction of open-high-low-close data in candlestick chart based on pseudo-PCA," Papers 2103.16908, arXiv.org.
  14. Wang, Yuhao & Chen, Huayou & Xu, Xuetao, 2025. "A weekly crude oil price interval-valued prediction architecture on fusion of decomposition technique and adaptive integration," Energy, Elsevier, vol. 334(C).
  15. Gloria Gonzalez‐Rivera & Yun Luo & Esther Ruiz, 2020. "Prediction regions for interval‐valued time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 373-390, June.
  16. Guo, Wei & Liu, Qingfu & Luo, Zhidan & Tse, Yiuman, 2022. "Forecasts for international financial series with VMD algorithms," Journal of Asian Economics, Elsevier, vol. 80(C).
  17. Feng Gao & Jie Song & Xueyan Shao, 2025. "Short-term interval-valued load forecasting with a combined strategy of iHW and multioutput machine learning," Annals of Operations Research, Springer, vol. 346(3), pages 2009-2033, March.
  18. Leandro Maciel, 2020. "Technical analysis based on high and low stock prices forecasts: evidence for Brazil using a fractionally cointegrated VAR model," Empirical Economics, Springer, vol. 58(4), pages 1513-1540, April.
  19. Leandro Maciel & Gustavo Yamachi & Vinicius Nazato & Fernando Gomide, 2025. "A Dynamic Fuzzy Modeling Method for Interval Time Series and Applications in Range‐Based Volatility Prediction," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(8), pages 2459-2477, December.
  20. González-Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2023. "Modelling intervals of minimum/maximum temperatures in the Iberian Peninsula," DES - Working Papers. Statistics and Econometrics. WS 37968, Universidad Carlos III de Madrid. Departamento de Estadística.
  21. Gloria Gonzalez-Rivera & Yun Luo & Esther Ruiz, 2018. "Prediction Regions for Interval-valued Time Series," Working Papers 201817, University of California at Riverside, Department of Economics.
  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. 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).
  24. Yan, Zichun & Tian, Fangzhu & Sun, Yuying & Wang, Shouyang, 2024. "A time-frequency-based interval decomposition ensemble method for forecasting gasoil prices under the trend of low-carbon development," Energy Economics, Elsevier, vol. 134(C).
  25. Dongbin Kim & Jaewook Lee & Hoki Kim, 2026. "Pattern-guided forecasting framework for metal price prediction with grouping decomposed series," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 12(1), pages 1-30, December.
  26. Leandro Maciel & Rosangela Ballini, 2021. "Functional Fuzzy Rule-Based Modeling for Interval-Valued Data: An Empirical Application for Exchange Rates Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 743-771, February.
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