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Daily Market News Sentiment and Stock Prices

Citations

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Cited by:

  1. Cai, Yi & Tang, Zhenpeng & Chen, Ying, 2024. "Can real-time investor sentiment help predict the high-frequency stock returns? Evidence from a mixed-frequency-rolling decomposition forecasting method," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
  2. Gambarelli, Luca & Muzzioli, Silvia, 2025. "News sentiment indicators and the cross-section of stock returns in the European stock market," International Review of Economics & Finance, Elsevier, vol. 101(C).
  3. Shahid Raza & Sun Baiqing & Pwint Kay-Khine & Muhammad Ali Kemal, 2023. "Uncovering the Effect of News Signals on Daily Stock Market Performance: An Econometric Analysis," IJFS, MDPI, vol. 11(3), pages 1-25, August.
  4. Seok, Sangik & Cho, Hoon & Ryu, Doojin, 2024. "Dual effects of investor sentiment and uncertainty in financial markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 300-315.
  5. Boufateh, Talel & Saadaoui, Zied & Jiao, Zhilun, 2025. "On the time-varying responses of Fintech stock returns to geopolitical, financial and market sentiment shocks," The Quarterly Review of Economics and Finance, Elsevier, vol. 101(C).
  6. Tang, Zhenpeng & Lin, Qiaofeng & Cai, Yi & Chen, Kaijie & Liu, Dinggao, 2024. "Harnessing the power of real-time forum opinion: Unveiling its impact on stock market dynamics using intraday high-frequency data in China," International Review of Financial Analysis, Elsevier, vol. 93(C).
  7. Seok, Sangik & Cho, Hoon & Ryu, Doojin, 2022. "Scheduled macroeconomic news announcements and intraday market sentiment," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
  8. Lukas Petrasek & Jiri Kukacka, 2025. "US equity announcement risk premia," Review of Quantitative Finance and Accounting, Springer, vol. 65(1), pages 345-363, July.
  9. Jiang, Jiaqi & Zhang, Zhipeng & Cheng, Gongpin, 2024. "Corporate violations, traditional media and stock returns: Evidence from Chinese listed companies," Finance Research Letters, Elsevier, vol. 69(PA).
  10. Tian Guo & Emmanuel Hauptmann, 2024. "Fine-Tuning Large Language Models for Stock Return Prediction Using Newsflow," Papers 2407.18103, arXiv.org, revised Aug 2024.
  11. Seetharam, Yudhvir & Nyakurukwa, Kingstone, 2024. "Do optimistic portfolios outperform pessimistic portfolios: Evidence from textual sentiment," Economics Letters, Elsevier, vol. 242(C).
  12. Farrell, Hugh & O'Connor, Fergal, 2025. "The CNN Fear and Greed Index as a predictor of US equity index returns: Static and time-varying Granger causality," Finance Research Letters, Elsevier, vol. 72(C).
  13. Na, Haejung & Kim, Soonho, 2021. "Predicting stock prices based on informed traders’ activities using deep neural networks," Economics Letters, Elsevier, vol. 204(C).
  14. David E. Allen & Michael McAleer & Abhay K. Singh, 2014. "Machine news and volatility: The Dow Jones Industrial Average and the TRNA sentiment series," Working Papers in Economics 14/04, University of Canterbury, Department of Economics and Finance.
  15. Mohamed Arbi Madani, 2025. "The S&P 500 sectoral indices responses to economic news sentiment," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 30(2), pages 2042-2060, April.
  16. Wang, Gaoshan & Yu, Guangjin & Shen, Xiaohong, 2021. "The effect of online environmental news on green industry stocks: The mediating role of investor sentiment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
  17. Zhang, Junhuan & Zhang, Ziyan & Wen, Jiaqi, 2025. "A multifactor model using large language models and multimodal investor sentiment," International Review of Economics & Finance, Elsevier, vol. 102(C).
  18. David E. Allen & Michael McAleer, 2019. "Fake News and Propaganda: Trump’s Democratic America and Hitler’s National Socialist (Nazi) Germany," Sustainability, MDPI, vol. 11(19), pages 1-19, September.
  19. Anca Ioana, Iacob (Troto), 2021. "Investor Sentiment - Theoretical Aspects And Practical Conclusions, In The Context Of The Pandemic Crisis," Management Strategies Journal, Constantin Brancoveanu University, vol. 51(1), pages 122-128.
  20. Krystian M. Zawadzki & Marcin Potrykus, 2023. "Stock Markets’ Reactions to the Announcement of the Hosts. An Event Study in the Analysis of Large Sporting Events in the Years 1976–2032," Journal of Sports Economics, , vol. 24(6), pages 759-800, August.
  21. Steven Buigut and Burcu Kapar, 2022. "Do COVID-19 Incidence and Government Intervention Influence Media Indices?," Bulletin of Applied Economics, Risk Market Journals, vol. 9(2), pages 79-100.
  22. Suchismita Mishra & Le Zhao, 2021. "Order Routing Decisions for a Fragmented Market: A Review," JRFM, MDPI, vol. 14(11), pages 1-32, November.
  23. Fabian Billert & Stefan Conrad, 2024. "A Framework for the Construction of a Sentiment-Driven Performance Index: The Case of DAX40," Papers 2409.20397, arXiv.org.
  24. Yao, Can-Zhong & Li, Hong-Yu, 2020. "Time-varying lead–lag structure between investor sentiment and stock market," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
  25. Durand, Robert B. & Khuu, Joyce & Smales, Lee A., 2023. "Lost in translation. When sentiment metrics for one market are derived from two different languages," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
  26. David E Allen & Michael McAleer & Abhay K Singh, 2017. "An entropy-based analysis of the relationship between the DOW JONES Index and the TRNA Sentiment series," Applied Economics, Taylor & Francis Journals, vol. 49(7), pages 677-692, February.
  27. Seok, Sang Ik & Cho, Hoon & Ryu, Doojin, 2021. "Stock Market’s responses to intraday investor sentiment," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
  28. Zihan Dong & Xinyu Fan & Zhiyuan Peng, 2024. "FNSPID: A Comprehensive Financial News Dataset in Time Series," Papers 2402.06698, arXiv.org.
  29. Xiaohong Shen & Gaoshan Wang & Yue Wang & Alfred Peris, 2021. "The Influence of Research Reports on Stock Returns: The Mediating Effect of Machine-Learning-Based Investor Sentiment," Discrete Dynamics in Nature and Society, Hindawi, vol. 2021, pages 1-14, December.
  30. Kao, Yu-Sheng & Day, Min-Yuh & Chou, Ke-Hsin, 2024. "A comparison of bitcoin futures return and return volatility based on news sentiment contemporaneously or lead-lag," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
  31. Chou, Ke-Hsin & Day, Min-Yuh & Chiu, Chien-Liang, 2023. "Do bitcoin news information flow and return volatility fit the sequential information arrival hypothesis and the mixture of distribution hypothesis?," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 365-385.
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