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Generative AI Use by Capital Market Information Intermediaries: Evidence from Seeking Alpha

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  • Mark T. Bradshaw
  • Chenyang Ma
  • Benjamin P. Yost
  • Yuan Zou

Abstract

We study the use of generative AI for firm‐specific financial analysis on the Seeking Alpha platform. After the initial launch of ChatGPT in November 2022, the share of AI‐generated articles rose sharply to 13.5% of all articles, then declined in late 2023 after Seeking Alpha equated the use of AI to plagiarism and announced a prohibition on its use. We organize our study around two questions: (1) Does AI use increase author productivity? and (2) does AI use have capital market consequences and ultimately affect the informational landscape? We find that authors who adopt AI become more productive, publishing more articles and covering more new firms than non‐adopters. Findings on AI article informativeness are more nuanced. On average, AI articles are less informative than human‐written articles, eliciting smaller trading volume and abnormal return responses. However, AI use leads to increased firm coverage and in turn to improved liquidity and faster price discovery. Our findings suggest that, while AI‐generated articles are currently perceived as less informative than human‐written articles, their comparatively low cost enables increased firm coverage and thereby improves the overall informational landscape.

Suggested Citation

  • Mark T. Bradshaw & Chenyang Ma & Benjamin P. Yost & Yuan Zou, 2026. "Generative AI Use by Capital Market Information Intermediaries: Evidence from Seeking Alpha," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 64(3), pages 1233-1286, June.
  • Handle: RePEc:bla:joares:v:64:y:2026:i:3:p:1233-1286
    DOI: 10.1111/1475-679x.70053
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    1. Wolfgang Breuer & Andreas Knetsch & Eric Sachsenhausen, 2025. "Influence and Predictive Value of Seeking Alpha Articles," Financial Analysts Journal, Taylor & Francis Journals, vol. 81(1), pages 102-128, January.
    2. Jonathan L. Rogers & Douglas J. Skinner & Sarah L. C. Zechman, 2016. "The role of the media in disseminating insider-trading news," Review of Accounting Studies, Springer, vol. 21(3), pages 711-739, September.
    3. Jeremy Bertomeu & Edwige Cheynel & Eric Floyd & Wenqiang Pan, 2021. "Using machine learning to detect misstatements," Review of Accounting Studies, Springer, vol. 26(2), pages 468-519, June.
    4. Joshua Mitts, 2020. "Short and Distort," The Journal of Legal Studies, University of Chicago Press, vol. 49(2), pages 287-334.
    5. John L. Campbell & Matthew D. DeAngelis & James R. Moon, 2019. "Skin in the game: personal stock holdings and investors’ response to stock analysis on social media," Review of Accounting Studies, Springer, vol. 24(3), pages 731-779, September.
    6. Agarwal, Vineet & Taffler, Richard, 2008. "Comparing the performance of market-based and accounting-based bankruptcy prediction models," Journal of Banking & Finance, Elsevier, vol. 32(8), pages 1541-1551, August.
    7. Nerissa C. Brown & Richard M. Crowley & W. Brooke Elliott, 2020. "What Are You Saying? Using topic to Detect Financial Misreporting," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 58(1), pages 237-291, March.
    8. Travis Dyer & Eunjee Kim, 2021. "Anonymous Equity Research," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 59(2), pages 575-611, May.
    9. Hans B. Christensen & Luzi Hail & Christian Leuz, 2016. "Capital-Market Effects of Securities Regulation: Prior Conditions, Implementation, and Enforcement," The Review of Financial Studies, Society for Financial Studies, vol. 29(11), pages 2885-2924.
    10. Ding, Rong & Zhou, Hang & Li, Yifan, 2020. "Social media, financial reporting opacity, and return comovement: Evidence from Seeking Alpha," Journal of Financial Markets, Elsevier, vol. 50(C).
    11. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    12. Umar, Tarik, 2022. "Complexity aversion when SeekingAlpha," Journal of Accounting and Economics, Elsevier, vol. 73(2).
    13. Xi Chen & Yang Ha (Tony) Cho & Yiwei Dou & Baruch Lev, 2022. "Predicting Future Earnings Changes Using Machine Learning and Detailed Financial Data," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 60(2), pages 467-515, May.
    14. Lev, B & Thiagarajan, Sr, 1993. "Fundamental Information Analysis," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 31(2), pages 190-215.
    15. Miao Liu, 2022. "Assessing Human Information Processing in Lending Decisions: A Machine Learning Approach," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 60(2), pages 607-651, May.
    16. Holger Daske & Luzi Hail & Christian Leuz & Rodrigo Verdi, 2008. "Mandatory IFRS Reporting around the World: Early Evidence on the Economic Consequences," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 46(5), pages 1085-1142, December.
    17. Mai, Feng & Tian, Shaonan & Lee, Chihoon & Ma, Ling, 2019. "Deep learning models for bankruptcy prediction using textual disclosures," European Journal of Operational Research, Elsevier, vol. 274(2), pages 743-758.
    18. Fried, Dov & Givoly, Dan, 1982. "Financial analysts' forecasts of earnings : A better surrogate for market expectations," Journal of Accounting and Economics, Elsevier, vol. 4(2), pages 85-107, October.
    19. Dim, Chukwuma, 2025. "Social Media Analysts’ Skill: Evidence from Text-Implied Beliefs," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 60(7), pages 3081-3115, November.
    20. Rong Ding & Yukun Shi & Hang Zhou, 2023. "Social media coverage and post-earnings announcement drift: evidence from seeking alpha," The European Journal of Finance, Taylor & Francis Journals, vol. 29(2), pages 207-227, January.
    21. Elizabeth Blankespoor & Ed deHaan & Christina Zhu, 2018. "Capital market effects of media synthesis and dissemination: evidence from robo-journalism," Review of Accounting Studies, Springer, vol. 23(1), pages 1-36, March.
    22. Normah Omar & Zulaikha ‘Amirah Johari & Malcolm Smith, 2017. "Predicting fraudulent financial reporting using artificial neural network," Journal of Financial Crime, Emerald Group Publishing Limited, vol. 24(2), pages 362-387, May.
    23. Brown, Lawrence D & Rozeff, Michael S, 1978. "The Superiority of Analyst Forecasts as Measures of Expectations: Evidence from Earnings," Journal of Finance, American Finance Association, vol. 33(1), pages 1-16, March.
    24. Brad M. Barber & Xing Huang & Philippe Jorion & Terrance Odean & Christopher Schwarz, 2024. "A (Sub)penny for Your Thoughts: Tracking Retail Investor Activity in TAQ," Journal of Finance, American Finance Association, vol. 79(4), pages 2403-2427, August.
    25. Robert M. Bushman & Abbie J. Smith & Regina Wittenberg‐Moerman, 2010. "Price Discovery and Dissemination of Private Information by Loan Syndicate Participants," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 48(5), pages 921-972, December.
    26. Qiyang He & Henry Leung & Buhui Qiu & Zhou Zhou, 2025. "The Effect of Social Media on Corporate Innovation: Evidence from Seeking Alpha Coverage," Management Science, INFORMS, vol. 71(7), pages 5441-5476, July.
    27. Bertomeu, Jeremy & Lin, Yupeng & Liu, Yibin & Ni, Zhenghui, 2025. "The impact of generative AI on information processing: Evidence from the ban of ChatGPT in Italy," Journal of Accounting and Economics, Elsevier, vol. 80(1).
    28. Ou, Jane A. & Penman, Stephen H., 1989. "Financial statement analysis and the prediction of stock returns," Journal of Accounting and Economics, Elsevier, vol. 11(4), pages 295-329, November.
    29. Dyer, Travis & Guest, Nicholas & Yu, Elisha, 2025. "New accounting standards and the performance of quantitative investors," Journal of Accounting and Economics, Elsevier, vol. 79(2).
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    Cited by:

    1. Elizabeth Blankespoor & Ed Dehaan & Qianqian Li, 2026. "Generative AI in Financial Reporting," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 64(3), pages 1189-1232, June.
    2. Sean Shun Cao & Wilbur Xinyuan Chen & Guang Ma & Suraj Srinivasan, 2026. "Generative AI in Capital Markets: Information Production, Dissemination, and Processing," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 64(3), pages 1427-1450, June.

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