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A novel text-based framework for forecasting agricultural futures using massive online news headlines

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Cited by:

  1. Sun, Jingyun & Zhao, Panpan & Sun, Shaolong, 2022. "A new secondary decomposition-reconstruction-ensemble approach for crude oil price forecasting," Resources Policy, Elsevier, vol. 77(C).
  2. Wen, Shigang & Li, Jianping & Huang, Chuangxia & Zhu, Xiaoqian, 2023. "Extreme risk spillovers among traditional financial and FinTech institutions: A complex network perspective," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 190-202.
  3. Si, Jingjian & Gao, Xiangyun & Zhou, Jinsheng, 2025. "Using deep learning to predict energy stock risk spillover based on co-investor attention," Finance Research Letters, Elsevier, vol. 74(C).
  4. 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.
  5. Ewald, Christian Oliver & Li, Yaoyu, 2024. "The role of news sentiment in salmon price prediction using deep learning," Journal of Commodity Markets, Elsevier, vol. 36(C).
  6. Lili Pan & Lin Wang & Qianqian Feng, 2022. "A Bibliometric Analysis of Risk Management in Foreign Direct Investment: Insights and Implications," Sustainability, MDPI, vol. 14(12), pages 1-18, June.
  7. Xiaoqian Zhu & Jianping Li & Yinghui Wang, 2024. "Are risk disclosures in financial reports informative? A text mining-based perspective," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-18, December.
  8. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
  9. Yuyao Feng & Guowen Li & Xiaolei Sun & Jianping Li, 2022. "Identification of tourists’ dynamic risk perception—the situation in Tibet," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-13, December.
  10. Jujie Wang & Zhenzhen Zhuang & Liu Feng, 2022. "Intelligent Optimization Based Multi-Factor Deep Learning Stock Selection Model and Quantitative Trading Strategy," Mathematics, MDPI, vol. 10(4), pages 1-19, February.
  11. Yunfei Xing & Justin Z. Zhang & Yuming He & Yueqi Li, 2025. "Toward an ecosystem of non-fungible tokens from mapping public opinions on social media," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-24, December.
  12. Zhang, Xin & Wang, Jujie & He, Xuecheng, 2025. "An optimal multi-scale ensemble transformer for carbon emission allowance price prediction based on time series patching and two-stage stabilization," Energy, Elsevier, vol. 328(C).
  13. Wuyue An & Lin Wang & Yu‐Rong Zeng, 2023. "Text‐based soybean futures price forecasting: A two‐stage deep learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 312-330, March.
  14. Li, Guowen & Jing, Zhongbo & Li, Jingyu & Feng, Yuyao, 2023. "Drivers of risk correlation among financial institutions: A study based on a textual risk disclosure perspective," Economic Modelling, Elsevier, vol. 128(C).
  15. Binrong Wu & Sihao Yu & Sheng‐Xiang Lv, 2025. "Explainable Soybean Futures Price Forecasting Based on Multi‐Source Feature Fusion," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(4), pages 1363-1382, July.
  16. Junshu Jiang & Jordan Richards & Raphael Huser & David Bolin, 2024. "The Efficient Tail Hypothesis: An Extreme Value Perspective on Market Efficiency," Papers 2408.06661, arXiv.org, revised Jul 2025.
  17. Xiaoqian Zhu & Yinghui Wang & Jianping Li, 2022. "What drives reputational risk? Evidence from textual risk disclosures in financial statements," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-15, December.
  18. Jiang, He & Hu, Weiqiang & Xiao, Ling & Dong, Yao, 2022. "A decomposition ensemble based deep learning approach for crude oil price forecasting," Resources Policy, Elsevier, vol. 78(C).
  19. Li, Guowen & Wang, Shuai & Feng, Yuyao, 2024. "Making differences work: Financial fraud detection based on multi-subject perceptions," Emerging Markets Review, Elsevier, vol. 60(C).
  20. Wuyue An & Lin Wang & Dongfeng Zhang, 2023. "Comprehensive commodity price forecasting framework using text mining methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1865-1888, November.
  21. Xu Gong & Keqin Guan & Qiyang Chen, 2022. "The role of textual analysis in oil futures price forecasting based on machine learning approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(10), pages 1987-2017, October.
  22. Li, Jingyu & Guo, Ce & Lv, Sijia & Xie, Qiwei & Zheng, Xiaolong, 2024. "Financial fraud detection for Chinese listed firms: Does managers' abnormal tone matter?," Emerging Markets Review, Elsevier, vol. 62(C).
  23. Mao, Jinqi & Wang, Delu & Chen, Fan & Li, Chunxiao & Shi, Xunpeng & Zhang, Yuqing, 2024. "A novel text-based framework for forecasting coal power overcapacity in China from the industrial correlation perspective," Technological Forecasting and Social Change, Elsevier, vol. 208(C).
  24. Hao, Jun & Feng, Qianqian & Yuan, Jiaxin & Sun, Xiaolei & Li, Jianping, 2022. "A dynamic ensemble learning with multi-objective optimization for oil prices prediction," Resources Policy, Elsevier, vol. 79(C).
  25. Li, Hengyun & Gao, Huicai & Song, Haiyan, 2023. "Tourism forecasting with granular sentiment analysis," Annals of Tourism Research, Elsevier, vol. 103(C).
  26. Xu Zhang & Xian Yang & Jianping Li & Jun Hao, 2023. "Contemporaneous and noncontemporaneous idiosyncratic risk spillovers in commodity futures markets: A novel network topology approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(6), pages 705-733, June.
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