Forecasting Oil Price Trends with Sentiment of Online News Articles
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DOI: 10.1142/S021759591740019X
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- Wang, Minggang & Chen, Ying & Tian, Lixin & Jiang, Shumin & Tian, Zihao & Du, Ruijin, 2016. "Fluctuation behavior analysis of international crude oil and gasoline price based on complex network perspective," Applied Energy, Elsevier, vol. 175(C), pages 109-127.
- Yu, Lean & Zhao, Yang & Tang, Ling, 2014. "A compressed sensing based AI learning paradigm for crude oil price forecasting," Energy Economics, Elsevier, vol. 46(C), pages 236-245.
- Smales, Lee A., 2014. "News sentiment in the gold futures market," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 275-286.
- Svetlana Borovkova & Diego Mahakena, 2015. "News, volatility and jumps: the case of natural gas futures," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1217-1242, July.
- Murat, Atilim & Tokat, Ekin, 2009. "Forecasting oil price movements with crack spread futures," Energy Economics, Elsevier, vol. 31(1), pages 85-90, January.
- Zhang, Xun & Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2009. "Estimating the impact of extreme events on crude oil price: An EMD-based event analysis method," Energy Economics, Elsevier, vol. 31(5), pages 768-778, September.
- Dhar, Tirtha & Weinberg, Charles B., 2016. "Measurement of interactions in non-linear marketing models: The effect of critics' ratings and consumer sentiment on movie demand," International Journal of Research in Marketing, Elsevier, vol. 33(2), pages 392-408.
- Giliola Frey & Matteo Manera & Anil Markandya & Elisa Scarpa, 2009. "Econometric Models for Oil Price Forecasting: A Critical Survey," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 10(01), pages 29-44, April.
- Jinn‐Yang Uang & David B. Citron & Sudi Sudarsanam & Richard J. Taffler, 2006. "Management Going‐concern Disclosures: Impact of Corporate Governance and Auditor Reputation," European Financial Management, European Financial Management Association, vol. 12(5), pages 789-816, November.
- Oladosu, Gbadebo, 2009. "Identifying the oil price-macroeconomy relationship: An empirical mode decomposition analysis of US data," Energy Policy, Elsevier, vol. 37(12), pages 5417-5426, December.
- Ling Tang & Wei Dai & Lean Yu & Shouyang Wang, 2015. "A Novel CEEMD-Based EELM Ensemble Learning Paradigm for Crude Oil Price Forecasting," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 14(01), pages 141-169.
- Ravi Kumar, P. & Ravi, V., 2007. "Bankruptcy prediction in banks and firms via statistical and intelligent techniques - A review," European Journal of Operational Research, Elsevier, vol. 180(1), pages 1-28, July.
- Lean Yu & Yang Zhao & Ling Tang, 2017. "Ensemble Forecasting for Complex Time Series Using Sparse Representation and Neural Networks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(2), pages 122-138, March.
- Tang, Ling & Yu, Lean & He, Kaijian, 2014. "A novel data-characteristic-driven modeling methodology for nuclear energy consumption forecasting," Applied Energy, Elsevier, vol. 128(C), pages 1-14.
- Movagharnejad, Kamyar & Mehdizadeh, Bahman & Banihashemi, Morteza & Kordkheili, Masoud Sheikhi, 2011. "Forecasting the differences between various commercial oil prices in the Persian Gulf region by neural network," Energy, Elsevier, vol. 36(7), pages 3979-3984.
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Cited by:
- He, Zhifang, 2020. "Dynamic impacts of crude oil price on Chinese investor sentiment: Nonlinear causality and time-varying effect," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 131-153.
- Atri, Hanen & Kouki, Saoussen & Gallali, Mohamed imen, 2021. "The impact of COVID-19 news, panic and media coverage on the oil and gold prices: An ARDL approach," Resources Policy, Elsevier, vol. 72(C).
- Jiangwei Liu & Xiaohong Huang, 2021. "Forecasting Crude Oil Price Using Event Extraction," Papers 2111.09111, arXiv.org.
- Wu, Yu-Xi & Wu, Qing-Biao & Zhu, Jia-Qi, 2019. "Improved EEMD-based crude oil price forecasting using LSTM networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 114-124.
- Paola Zola & Paulo Cortez & Costantino Ragno & Eugenio Brentari, 2019. "Social Media Cross-Source and Cross-Domain Sentiment Classification," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(05), pages 1469-1499, September.
- Lin, Ling & Jiang, Yong & Xiao, Helu & Zhou, Zhongbao, 2020. "Crude oil price forecasting based on a novel hybrid long memory GARCH-M and wavelet analysis model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 543(C).
- Lucey, Brian & Ren, Boru, 2021. "Does news tone help forecast oil?," Economic Modelling, Elsevier, vol. 104(C).
- 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.
- Mimoun Benali & Lahboub Karima, 2024. "Modelling Stock Prices of Energy Sector using Supervised Machine Learning Techniques," International Journal of Energy Economics and Policy, Econjournals, vol. 14(2), pages 594-602, March.
- 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).
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Keywords
Sentiment analysis; big data; text mining; oil price; trend prediction; online news;All these keywords.
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