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On the predictive ability of narrative disclosures in annual reports

Citations

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Cited by:

  1. Yubin Qian & Ya Sun, 2021. "The Correlation Between Annual Reports’ Narratives and Business Performance: A Retrospective Analysis," SAGE Open, , vol. 11(3), pages 21582440211, July.
  2. Kamaladdin Fataliyev & Aneesh Chivukula & Mukesh Prasad & Wei Liu, 2021. "Stock Market Analysis with Text Data: A Review," Papers 2106.12985, arXiv.org, revised Jul 2021.
  3. Gaizka Garechana & Rosa Río-Belver & Iñaki Bildosola & Marisela Rodríguez Salvador, 2017. "Effects of innovation management system standardization on firms: evidence from text mining annual reports," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1987-1999, June.
  4. Xue Wen Tan & Stanley Kok, 2024. "Explainable Risk Classification in Financial Reports," Papers 2405.01881, arXiv.org, revised May 2024.
  5. William L. Smith & David M. Boje & Kevin D. Melendrez, 2010. "The financial crisis and mark‐to‐market accounting," Qualitative Research in Accounting & Management, Emerald Group Publishing Limited, vol. 7(3), pages 281-303, August.
  6. Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2017. "A multidisciplinary perspective of big data in management research," International Journal of Production Economics, Elsevier, vol. 191(C), pages 97-112.
  7. Matteo Cinelli & Valerio Ficcadenti & Jessica Riccioni, 2021. "The interconnectedness of the economic content in the speeches of the US Presidents," Annals of Operations Research, Springer, vol. 299(1), pages 593-615, April.
  8. Pitschner, Stefan, 2020. "How do firms set prices? Narrative evidence from corporate filings," European Economic Review, Elsevier, vol. 124(C).
  9. Amy Richter & Kelvin Tsun Wai Ng & Bahareh Fallah, 2019. "Bibliometric and text mining approaches to evaluate landfill design standards," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 1027-1049, March.
  10. Peter M. Clarkson & Jordan Ponn & Gordon D. Richardson & Frank Rudzicz & Albert Tsang & Jingjing Wang, 2020. "A Textual Analysis of US Corporate Social Responsibility Reports," Abacus, Accounting Foundation, University of Sydney, vol. 56(1), pages 3-34, March.
  11. Stefan Feuerriegel & Helmut Prendinger, 2018. "News-based trading strategies," Papers 1807.06824, arXiv.org.
  12. Gehan A. Mousa & Elsayed A. H. Elamir & Khaled Hussainey, 2022. "Using machine learning methods to predict financial performance: Does disclosure tone matter?," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 19(1), pages 93-112, March.
  13. Alasdair Reid, 2023. "Closing the Affordable Housing Gap: Identifying the Barriers Hindering the Sustainable Design and Construction of Affordable Homes," Sustainability, MDPI, vol. 15(11), pages 1-27, May.
  14. Lifang Zhang & Mohammad Zoynul Abedin & Zhenkun Liu, 2024. "Incorporating media news to predict financial distress: Case study on Chinese listed companies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1374-1398, August.
  15. Tsai, Ming-Feng & Wang, Chuan-Ju, 2017. "On the risk prediction and analysis of soft information in finance reports," European Journal of Operational Research, Elsevier, vol. 257(1), pages 243-250.
  16. David F. Larcker & Anastasia A. Zakolyukina, 2012. "Detecting Deceptive Discussions in Conference Calls," Journal of Accounting Research, Wiley Blackwell, vol. 50(2), pages 495-540, May.
  17. Brent McKENZIE, 2021. "Retail Brand Evolution: The Case of Tallinna Kaubamaja Estonia’s Department Store," Journal of Emerging Trends in Marketing and Management, The Bucharest University of Economic Studies, vol. 1(1), pages 99-109, August.
  18. Katsafados, Apostolos G. & Androutsopoulos, Ion & Chalkidis, Ilias & Fergadiotis, Manos & Leledakis, George N. & Pyrgiotakis, Emmanouil G., 2020. "Textual Information and IPO Underpricing: A Machine Learning Approach," MPRA Paper 103813, University Library of Munich, Germany.
  19. Sagarika Mishra & Michael T. Ewing & Holly B. Cooper, 2022. "Artificial intelligence focus and firm performance," Journal of the Academy of Marketing Science, Springer, vol. 50(6), pages 1176-1197, November.
  20. Apostolos G. Katsafados & Dimitris Anastasiou, 2024. "Short-term prediction of bank deposit flows: do textual features matter?," Annals of Operations Research, Springer, vol. 338(2), pages 947-972, July.
  21. Ian D. Gow & Steven N. Kaplan & David F. Larcker & Anastasia A. Zakolyukina, 2016. "CEO Personality and Firm Policies," NBER Working Papers 22435, National Bureau of Economic Research, Inc.
  22. Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2019. "Technology in the 21st century: New challenges and opportunities," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 321-335.
  23. Mengke Qiao & Ke-Wei Huang, 2021. "Correcting Misclassification Bias in Regression Models with Variables Generated via Data Mining," Information Systems Research, INFORMS, vol. 32(2), pages 462-480, June.
  24. 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.
  25. Matteo Cinelli & Valerio Ficcadenti & Jessica Riccioni, 2020. "The interconnectedness of the economic content in the speeches of the US Presidents," Papers 2002.07880, arXiv.org.
  26. Chung, Wingyan, 2014. "BizPro: Extracting and categorizing business intelligence factors from textual news articles," International Journal of Information Management, Elsevier, vol. 34(2), pages 272-284.
  27. 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.
  28. Katsafados, Apostolos G. & Leledakis, George N. & Pyrgiotakis, Emmanouil G. & Androutsopoulos, Ion & Fergadiotis, Manos, 2024. "Machine learning in bank merger prediction: A text-based approach," European Journal of Operational Research, Elsevier, vol. 312(2), pages 783-797.
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