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Good debt or bad debt: Detecting semantic orientations in economic texts

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Cited by:

  1. Chen, Cathy Yi-Hsuan & Fengler, Matthias R. & Härdle, Wolfgang Karl & Liu, Yanchu, 2022. "Media-expressed tone, option characteristics, and stock return predictability," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
  2. Yi-Hsuan Chen, Cathy & Fengler, Matthias & Härdle, Wolfgang Karl & Liu, Yanchu, 2018. "Textual Sentiment, Option Characteristics, and Stock Return Predictability," Economics Working Paper Series 1808, University of St. Gallen, School of Economics and Political Science.
  3. Travis Adams & Andrea Ajello & Diego Silva & Francisco Vazquez-Grande, 2023. "More than Words: Twitter Chatter and Financial Market Sentiment," Papers 2305.16164, arXiv.org.
  4. Paola Cerchiello & Giancarlo Nicola, 2017. "Assessing News Contagion in Finance," DEM Working Papers Series 139, University of Pavia, Department of Economics and Management.
  5. Paola Cerchiello & Giancarlo Nicola & Samuel Rönnqvist & Peter Sarlin, 2017. "Deep Learning Bank Distress from News and Numerical Financial Data," DEM Working Papers Series 140, University of Pavia, Department of Economics and Management.
  6. Neng Wang & Hongyang Yang & Christina Dan Wang, 2023. "FinGPT: Instruction Tuning Benchmark for Open-Source Large Language Models in Financial Datasets," Papers 2310.04793, arXiv.org, revised Nov 2023.
  7. Boyu Zhang & Hongyang Yang & Tianyu Zhou & Ali Babar & Xiao-Yang Liu, 2023. "Enhancing Financial Sentiment Analysis via Retrieval Augmented Large Language Models," Papers 2310.04027, arXiv.org, revised Nov 2023.
  8. Chandan Singh & Armin Askari & Rich Caruana & Jianfeng Gao, 2023. "Augmenting interpretable models with large language models during training," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
  9. Ankur Sinha & Satishwar Kedas & Rishu Kumar & Pekka Malo, 2022. "SEntFiN 1.0: Entity‐aware sentiment analysis for financial news," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(9), pages 1314-1335, September.
  10. Jozef Barunik & Cathy Yi-Hsuan Chen & Jan Vecer, 2019. "Sentiment-Driven Stochastic Volatility Model: A High-Frequency Textual Tool for Economists," Papers 1906.00059, arXiv.org.
  11. Yong Xie & Dakuo Wang & Pin-Yu Chen & Jinjun Xiong & Sijia Liu & Sanmi Koyejo, 2022. "A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Predictions," Papers 2205.01094, arXiv.org, revised Jul 2022.
  12. Costola, Michele & Hinz, Oliver & Nofer, Michael & Pelizzon, Loriana, 2023. "Machine learning sentiment analysis, COVID-19 news and stock market reactions," Research in International Business and Finance, Elsevier, vol. 64(C).
  13. Tingsong Jiang & Andy Zeng, 2023. "Financial sentiment analysis using FinBERT with application in predicting stock movement," Papers 2306.02136, arXiv.org.
  14. Asier Guti'errez-Fandi~no & Miquel Noguer i Alonso & Petter Kolm & Jordi Armengol-Estap'e, 2021. "FinEAS: Financial Embedding Analysis of Sentiment," Papers 2111.00526, arXiv.org, revised Nov 2021.
  15. Bledar Fazlija & Pedro Harder, 2022. "Using Financial News Sentiment for Stock Price Direction Prediction," Mathematics, MDPI, vol. 10(13), pages 1-20, June.
  16. David M. Goldberg & Nohel Zaman & Arin Brahma & Mariano Aloiso, 2022. "Are mortgage loan closing delay risks predictable? A predictive analysis using text mining on discussion threads," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(3), pages 419-437, March.
  17. Andrea Ajello & Diego Silva & Travis Adams & Francisco Vazquez-Grande, 2023. "More than Words: Twitter Chatter and Financial Market Sentiment," Finance and Economics Discussion Series 2023-034, Board of Governors of the Federal Reserve System (U.S.).
  18. Ingrid E. Fisher & Margaret R. Garnsey & Mark E. Hughes, 2016. "Natural Language Processing in Accounting, Auditing and Finance: A Synthesis of the Literature with a Roadmap for Future Research," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(3), pages 157-214, July.
  19. Xiao-Yang Liu & Guoxuan Wang & Hongyang Yang & Daochen Zha, 2023. "FinGPT: Democratizing Internet-scale Data for Financial Large Language Models," Papers 2307.10485, arXiv.org, revised Nov 2023.
  20. Agam Shah & Arnav Hiray & Pratvi Shah & Arkaprabha Banerjee & Anushka Singh & Dheeraj Eidnani & Bhaskar Chaudhury & Sudheer Chava, 2024. "Numerical Claim Detection in Finance: A New Financial Dataset, Weak-Supervision Model, and Market Analysis," Papers 2402.11728, arXiv.org.
  21. Wehrheim, Lino, 2021. "The sound of silence: On the (in)visibility of economists in the media," Working Papers 30, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
  22. Mantas Lukauskas & Vaida Pilinkienė & Jurgita Bruneckienė & Alina Stundžienė & Andrius Grybauskas & Tomas Ruzgas, 2022. "Economic Activity Forecasting Based on the Sentiment Analysis of News," Mathematics, MDPI, vol. 10(19), pages 1-22, September.
  23. Kirtac, Kemal & Germano, Guido, 2024. "Sentiment trading with large language models," LSE Research Online Documents on Economics 122592, London School of Economics and Political Science, LSE Library.
  24. Agam Shah & Sudheer Chava, 2023. "Zero is Not Hero Yet: Benchmarking Zero-Shot Performance of LLMs for Financial Tasks," Papers 2305.16633, arXiv.org.
  25. 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.
  26. Priyank Sonkiya & Vikas Bajpai & Anukriti Bansal, 2021. "Stock price prediction using BERT and GAN," Papers 2107.09055, arXiv.org.
  27. Samuel Ronnqvist & Peter Sarlin, 2016. "Bank distress in the news: Describing events through deep learning," Papers 1603.05670, arXiv.org, revised Dec 2016.
  28. Alex Kim & Sangwon Yoon, 2023. "Corporate Bankruptcy Prediction with Domain-Adapted BERT," Papers 2312.03194, arXiv.org.
  29. Sinha, Ankur & Kedas, Satishwar & Kumar, Rishu & Malo, Pekka, 2019. "Buy, Sell or Hold: Entity-Aware Classification of Business News," IIMA Working Papers WP 2019-04-02, Indian Institute of Management Ahmedabad, Research and Publication Department.
  30. Bommes, Elisabeth & Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl, 2018. "Textual Sentiment and Sector specific reaction," IRTG 1792 Discussion Papers 2018-043, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  31. Yi Yang & Yixuan Tang & Kar Yan Tam, 2023. "InvestLM: A Large Language Model for Investment using Financial Domain Instruction Tuning," Papers 2309.13064, arXiv.org.
  32. Paola Cerchiello & Giancarlo Nicola, 2018. "Assessing News Contagion in Finance," Econometrics, MDPI, vol. 6(1), pages 1-19, February.
  33. Jean Lee & Nicholas Stevens & Soyeon Caren Han & Minseok Song, 2024. "A Survey of Large Language Models in Finance (FinLLMs)," Papers 2402.02315, arXiv.org.
  34. Boyu Zhang & Hongyang Yang & Xiao-Yang Liu, 2023. "Instruct-FinGPT: Financial Sentiment Analysis by Instruction Tuning of General-Purpose Large Language Models," Papers 2306.12659, arXiv.org.
  35. Runmei Luo & Yong Ye, 2024. "Pressure from words: The tone of investors in Chinese earnings communication conferences and managerial myopia," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(1), pages 833-868, March.
  36. Leippold, Markus, 2023. "Sentiment spin: Attacking financial sentiment with GPT-3," Finance Research Letters, Elsevier, vol. 55(PB).
  37. Thomas R. Cook & Sophia Kazinnik & Anne Lundgaard Hansen & Peter McAdam, 2023. "Evaluating Local Language Models: An Application to Bank Earnings Calls," Research Working Paper RWP 23-12, Federal Reserve Bank of Kansas City.
  38. Duygu Ider & Stefan Lessmann, 2022. "Forecasting Cryptocurrency Returns from Sentiment Signals: An Analysis of BERT Classifiers and Weak Supervision," Papers 2204.05781, arXiv.org, revised Mar 2023.
  39. Moritz Scherrmann, 2023. "Multi-Label Topic Model for Financial Textual Data," Papers 2311.07598, arXiv.org.
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