Coupling News Sentiment with Web Browsing Data Improves Prediction of Intra-Day Price Dynamics
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DOI: 10.1371/journal.pone.0146576
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Cited by:
- Mario Gutiérrez-Roig & Carlota Segura & Jordi Duch & Josep Perelló, 2016. "Market Imitation and Win-Stay Lose-Shift Strategies Emerge as Unintended Patterns in Market Direction Guesses," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-19, August.
- Agarwal, Arvind & Gupta, Aparna & Kumar, Arun & Tamilselvam, Srikanth G., 2019. "Learning risk culture of banks using news analytics," European Journal of Operational Research, Elsevier, vol. 277(2), pages 770-783.
- Zhen-Hua Yang & Jian-Guo Liu & Chang-Rui Yu & Jing-Ti Han, 2017. "Quantifying the effect of investors’ attention on stock market," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-16, May.
- Ana Fern'andez Vilas & Rebeca D'iaz Redondo & Ant'on Lorenzo Garc'ia, 2023. "The irruption of cryptocurrencies into Twitter cashtags: a classifying solution," Papers 2312.11531, arXiv.org.
- Shen, Dehua & Liu, Lanbiao & Zhang, Yongjie, 2018. "Quantifying the cross-sectional relationship between online sentiment and the skewness of stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 928-934.
- Danilo Vassallo & Giacomo Bormetti & Fabrizio Lillo, 2019. "A tale of two sentiment scales: Disentangling short-run and long-run components in multivariate sentiment dynamics," Papers 1910.01407, arXiv.org, revised Sep 2020.
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