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There are multiple sources of financial news online which influence market movements and trader's decisions.
P. J. Stone, D. C. Dunphy, M. S. Smith, and D. M. Ogilvie, The General Inquirer: A Computer Approach to Content Analysis . MIT Press, 1966
1966
Earlier work this paper cites.
E. F. Fama, “Efficient capital markets: A review of theory and empirical work,” The Journal of Finance , vol. 25, no. 2, pp. 383–417, 1970
1970
Earlier work this paper cites.
N. Cristianini and J. Shawe-Taylor, An introduction to support vector machines and other kernel-based learning methods . Cambridge University Press, 2000
2000
Earlier work this paper cites.
T. Loughran and B. Mcdonald, “When is a liability not a liability? Textual analysis, dictionaries, and 10-Ks,” The Journal of Finance , vol. 66, pp. 35 – 65, 02 2011
2011
Earlier work this paper cites.
X. Li, H. Xie, L. Chen, J. Wang, and X. Deng, “News impact on stock price return via sentiment analysis,” Knowledge-Based Systems , vol. 69, pp. 14–23, 2014
2014
Earlier work this paper cites.
C. Hutto and E. Gilbert, “VADER: A parsimonious rule-based model for sentiment analysis of social media text,” vol. 08, no. 01. Proceedings of the 8th International Conference on Weblogs and Social Media, ICWSM 2014, 2015, pp. 216–225
2015
Earlier work this paper cites.
Z. Yang, D. Yang, C. Dyer, X. He, A. Smola, and E. Hovy, “Hierarchical attention networks for document classification,” 01 2016, pp. 1480–1489
2016
Earlier work this paper cites.
2017
Earlier work this paper cites.
Z. T. Ke, B. T. Kelly, and D. Xiu, “Predicting returns with text data,” National Bureau of Economic Research, Tech. Rep., 2019
2019
Cited alongside, same era.
J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova, “BERT: Pre-training of deep bidirectional transformers for language understanding,” in North American Chapter of the Association for Computational Linguistics , 2019. [Online]. Available: https://api.semanticscholar.org/CorpusID:52967399
2019
Cited alongside, same era.
2019
Cited alongside, same era.
Z. T. Ke, B. T. Kelly, and D. Xiu, “Predicting returns with text data,” National Bureau of Economic Research, Inc, NBER Working Papers 26186, 2019. [Online]. Available: https://EconPapers.repec.org/RePEc:nbr:nberwo:26186
2019
Cited alongside, same era.
2023
Later among the works it cites.
Z. Chen, S. Gössi, W. Kim, B. Bermeitinger, and S. Handschuh, “FinBERT-FOMC: Fine-tuned FinBERT Model with sentiment focus method for enhancing sentiment analysis of FOMC minutes.” Proceedings of the 4th ACM International Conference on AI in Finance, 2023, pp. 357–364
2023
Later among the works it cites.
2023
Later among the works it cites.
2023
Later among the works it cites.
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J. B. Berk and P. M. DeMarzo, “Corporate finance,” vol. 5, 2019
2019
Cited alongside, same era.
K. Mishev, A. Gjorgjevikj, I. Vodenska, L. T. Chitkushev, and D. Trajanov, “Evaluation of sentiment analysis in finance: From lexicons to transformers,” IEEE Access , vol. 8, pp. 131 662–131 682, 07 2020
2020
Cited alongside, same era.
2021
Cited alongside, same era.
2023
Later among the works it cites.
2023
Later among the works it cites.
Yahoo Finance, “Treasury yield 10 years historical data.” 2023. [Online]. Available: https://finance.yahoo.com/quote/%5ETNX/history
2023
Later among the works it cites.