IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v254y2025ics0165176525002411.html

Predicting stock price trends using language models to extract the sentiment from analyst reports: Evidence from IBEX 35-listed companies

Author

Listed:
  • Moreno, Alejandro
  • Ordieres-Meré, Joaquín

Abstract

This study investigates the utility of large language models to extract sentiment from sell-side equity analysts’ reports and their potential ability to predict stock price trends, using the IBEX 35 index as a case study. The RoBERTa, FinBERT, and GPT natural language processing models are employed to analyze a corpus of analysts’ equity research reports over 2016–2022. The results indicate that the extracted sentiment can serve as a valuable tool for forecasting stock price movements, avoiding the potential bias in analyst reports when assigning a target price. This highlights the transformative potential of language models in the financial industry and their role in assisting investors in making informed investment decisions.

Suggested Citation

  • Moreno, Alejandro & Ordieres-Meré, Joaquín, 2025. "Predicting stock price trends using language models to extract the sentiment from analyst reports: Evidence from IBEX 35-listed companies," Economics Letters, Elsevier, vol. 254(C).
    • Handle: RePEc:eee:ecolet:v:254:y:2025:i:c:s0165176525002411
    DOI: 10.1016/j.econlet.2025.112404
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176525002411
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2025.112404?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Li, Tao, 2022. "Analyst's stock views and revision actions," Finance Research Letters, Elsevier, vol. 44(C).
    2. William Beaver & Bradford Cornell & Wayne R. Landsman & Stephen R. Stubben, 2008. "The Impact of Analysts' Forecast Errors and Forecast Revisions on Stock Prices," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 35(5-6), pages 709-740.
    3. Huai-Chun Lo, 2017. "Do Firm Size Influence Financial Analyst Research Reports and Subsequent Stock Performance," Accounting and Finance Research, Sciedu Press, vol. 6(4), pages 181-181, Novebmer.
    4. Bandyopadhyay, Sati P. & Brown, Lawrence D. & Richardson, Gordon D., 1995. "Analysts' use of earnings forecasts in predicting stock returns: Forecast horizon effects," International Journal of Forecasting, Elsevier, vol. 11(3), pages 429-445, September.
    5. Morgan, John & Stocken, Phillip C, 2003. "An Analysis of Stock Recommendations," RAND Journal of Economics, The RAND Corporation, vol. 34(1), pages 183-203, Spring.
    6. Karmaziene, Egle, 2023. "The greater the volume, the greater the analyst," Finance Research Letters, Elsevier, vol. 51(C).
    7. Lawrence D. Brown & Andrew C. Call & Michael B. Clement & Nathan Y. Sharp, 2015. "Inside the “Black Box” of Sell‐Side Financial Analysts," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 53(1), pages 1-47, March.
    8. Eric Brown, 1999. "A Non‐Random Walk Down Wall Street," Journal of Economic Surveys, Wiley Blackwell, vol. 13(4), pages 477-478, September.
    9. Hou, Yunfei & Hu, Changsheng, 2023. "Understanding the role of aggregate analyst attention in resolving stock market uncertainty," Finance Research Letters, Elsevier, vol. 57(C).
    10. Steve J. Bickley & Ho Fai Chan & Benno Torgler, 2022. "Artificial intelligence in the field of economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 2055-2084, April.
    11. Frijns, Bart & Garel, Alexandre, 2021. "The effect of cultural distance between an analyst and a CEO on analysts’ earnings forecast performance," Economics Letters, Elsevier, vol. 205(C).
    12. Kirtac, Kemal & Germano, Guido, 2024. "Sentiment trading with large language models," Finance Research Letters, Elsevier, vol. 62(PB).
    13. Nyakurukwa, Kingstone & Seetharam, Yudhvir, 2023. "Can textual sentiment partially explain differences in the prices of dual-listed stocks?," Finance Research Letters, Elsevier, vol. 58(PC).
    14. Shaen Corbet & Michael Dowling & Mark Cummins, 2015. "Analyst recommendations and volatility in a rising, falling, and crisis equity market," Post-Print hal-04028662, HAL.
    15. Rybinski, Krzysztof, 2020. "The forecasting power of the multi-language narrative of sell-side research: A machine learning evaluation," Finance Research Letters, Elsevier, vol. 34(C).
    16. Tim Loughran & Bill McDonald, 2020. "Textual Analysis in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 12(1), pages 357-375, December.
    17. Shijie Wu & Ozan Irsoy & Steven Lu & Vadim Dabravolski & Mark Dredze & Sebastian Gehrmann & Prabhanjan Kambadur & David Rosenberg & Gideon Mann, 2023. "BloombergGPT: A Large Language Model for Finance," Papers 2303.17564, arXiv.org, revised Dec 2023.
    18. Tomasz Piotr Wisniewski & Liafisu Sina Yekini, 2015. "Stock market returns and the content of annual report narratives," Accounting Forum, Taylor & Francis Journals, vol. 39(4), pages 281-294, December.
    19. Grant, Andrew & Jarnecic, Elvis & Su, Mark, 2015. "Asymmetric effects of sell-side analyst optimism and broker market share by clientele," Journal of Financial Markets, Elsevier, vol. 24(C), pages 49-65.
    20. Corbet, Shaen & Dowling, Michael & Cummins, Mark, 2015. "Analyst recommendations and volatility in a rising, falling, and crisis equity market," Finance Research Letters, Elsevier, vol. 15(C), pages 187-194.
    21. Sean Cao & Wei Jiang & Junbo L. Wang & Baozhong Yang, 2021. "From Man vs. Machine to Man + Machine: The Art and AI of Stock Analyses," NBER Working Papers 28800, National Bureau of Economic Research, Inc.
    22. Jaroslav Bukovina, 2015. "Sentiment and blue-chip returns. Firm level evidence from a dynamic threshold model," MENDELU Working Papers in Business and Economics 2015-53, Mendel University in Brno, Faculty of Business and Economics.
    23. Abarbanell, JS & Bushee, BJ, 1997. "Fundamental analysis, future earnings, and stock prices," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 35(1), pages 1-24.
    24. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    25. Le, Thanh Dat & Trinh, Tri, 2022. "Distracted analysts and earnings management," Finance Research Letters, Elsevier, vol. 49(C).
    26. Johan Graaf, 2023. "Can Sell-side Analysts Compete Using Public Information? Analysts as Frame-makers Revisited," European Accounting Review, Taylor & Francis Journals, vol. 32(1), pages 141-167, January.
    27. William Beaver & Bradford Cornell & Wayne R. Landsman & Stephen R. Stubben, 2008. "The Impact of Analysts' Forecast Errors and Forecast Revisions on Stock Prices," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 35(5‐6), pages 709-740, June.
    28. Selin Duz Tan & Oktay Tas, 2021. "Social Media Sentiment in International Stock Returns and Trading Activity," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 22(2), pages 221-234, April.
    29. Bradley, Daniel & Gokkaya, Sinan & Liu, Xi & Xie, Fei, 2017. "Are all analysts created equal? Industry expertise and monitoring effectiveness of financial analysts," Journal of Accounting and Economics, Elsevier, vol. 63(2), pages 179-206.
    30. Gao, Kaijuan & Lin, Wanfa & Yang, Li & Chan, Kam C., 2020. "The impact of analyst coverage and stock price synchronicity: Evidence from brokerage mergers and closures✰," Finance Research Letters, Elsevier, vol. 33(C).
    31. Kim, Sehee & Lee, Woo-Jong & Park, Sunyoung & Sunwoo, Hee-Yeon, 2022. "Busy analysts in uncertain times," Finance Research Letters, Elsevier, vol. 46(PB).
    32. Markowitz, Harry M, 1991. "Foundations of Portfolio Theory," Journal of Finance, American Finance Association, vol. 46(2), pages 469-477, June.
    33. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, February.
    34. Pelster, Matthias & Val, Joel, 2024. "Can ChatGPT assist in picking stocks?," Finance Research Letters, Elsevier, vol. 59(C).
    35. Mark T. Bradshaw & Lawrence D. Brown & Kelly Huang, 2013. "Do sell-side analysts exhibit differential target price forecasting ability?," Review of Accounting Studies, Springer, vol. 18(4), pages 930-955, December.
    36. Stefan Pasch & Daniel Ehnes, 2022. "StonkBERT: Can Language Models Predict Medium-Run Stock Price Movements?," Papers 2202.02268, arXiv.org.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hou, Yunfei & Hu, Changsheng, 2023. "Understanding the role of aggregate analyst attention in resolving stock market uncertainty," Finance Research Letters, Elsevier, vol. 57(C).
    2. Dong, Mengming Michael & Stratopoulos, Theophanis C. & Wang, Victor Xiaoqi, 2024. "A scoping review of ChatGPT research in accounting and finance," International Journal of Accounting Information Systems, Elsevier, vol. 55(C).
    3. Thanos Konstantinidis & Giorgos Iacovides & Mingxue Xu & Tony G. Constantinides & Danilo Mandic, 2024. "FinLlama: Financial Sentiment Classification for Algorithmic Trading Applications," Papers 2403.12285, arXiv.org.
    4. Maher Hamid, 2026. "Implementing domain-specific LLMs for strategic investment decisions: a retrospective case study comparing AI and human expertise," Digital Finance, Springer, vol. 8(1), pages 1-134, March.
    5. Goodell, John W. & Kumar, Satish & Lim, Weng Marc & Pattnaik, Debidutta, 2021. "Artificial intelligence and machine learning in finance: Identifying foundations, themes, and research clusters from bibliometric analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    6. Abdi, Farshid & Kormanyos, Emily & Pelizzon, Loriana & Getmansky, Mila & Simon, Zorka, 2021. "Market impact of government communication: The case of presidential tweets," SAFE Working Paper Series 314, Leibniz Institute for Financial Research SAFE, revised 2021.
    7. Lars Hornuf & David J. Streich & Niklas Töllich, 2025. "Making GenAI Smarter: Evidence from a Portfolio Allocation Experiment," CESifo Working Paper Series 11862, CESifo.
    8. Sharneet Singh Jagirdar & Pradeep Kumar Gupta, 2023. "Value and Contrarian Investment Strategies: Evidence from Indian Stock Market," JRFM, MDPI, vol. 16(2), pages 1-19, February.
    9. Stolowy, Hervé & Paugam, Luc & Gendron, Yves, 2022. "Competing for narrative authority in capital markets: Activist short sellers vs. financial analysts," Accounting, Organizations and Society, Elsevier, vol. 100(C).
    10. Rizzo, Emanuele, 2018. "Essays on corporate governance and the impact of regulation on financial markets," Other publications TiSEM b5158260-ea13-4763-b992-6, Tilburg University, School of Economics and Management.
    11. Hiromasa Nakatsuka & Yoshiyuki Suimon, 2025. "Extracting information and sentiment analysis on dialogue in financial results briefing," Digital Finance, Springer, vol. 7(4), pages 605-621, December.
    12. Joon Chul James Ahn & Dragos Gorduza & Seonho Park, 2024. "Hidden neighbours: extracting industry momentum from stock networks," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 38(4), pages 415-441, December.
    13. Zhang, Wei & Shen, Dehua & Zhang, Yongjie & Xiong, Xiong, 2013. "Open source information, investor attention, and asset pricing," Economic Modelling, Elsevier, vol. 33(C), pages 613-619.
    14. Erica Juvercina Sobrinho & Rodrigo Fernandes Malaquias, 2025. "Government Announcements Through Harvest Reports, Extreme Market Conditions, and Commodity Price Volatility," Commodities, MDPI, vol. 4(4), pages 1-16, September.
    15. Dat Mai, 2024. "StockGPT: A GenAI Model for Stock Prediction and Trading," Papers 2404.05101, arXiv.org, revised Oct 2024.
    16. Kewei Hou & Haitao Mo & Chen Xue & Lu Zhang, 2024. "The Economics of Security Analysis," Management Science, INFORMS, vol. 70(1), pages 164-186, January.
    17. Duan, Mingli, 2025. "The signaling effect of tone: The influence of key audit matters’ tone on bank lending decisions," Finance Research Letters, Elsevier, vol. 76(C).
    18. Hamza Bennani & Cécile Couharde & Yoan Wallois, 2024. "The effect of IMF communication on government bond markets: insights from sentiment analysis," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 160(2), pages 615-656, May.
    19. Tsung-Jui Chiang-Lin & Yong-Shiuan Lee & Tzong-Hann Shieh & Chien-Chang Yen & Shang-Yueh Tsai, 2022. "Study of Asian indexes by a newly derived dynamic model," PLOS ONE, Public Library of Science, vol. 17(5), pages 1-19, May.
    20. Diego Pitta Jesus & Elvira Helena Oliveira Medeiros & Lucas Lúcio Godeiro & Andressa Lemes Proque, 2025. "Forecasting Brazilian Stock Market Using Sentiment Indices from Textual Data, Chat-GPT-Based and Technical Indicators," Computational Economics, Springer;Society for Computational Economics, vol. 66(5), pages 3735-3780, November.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecolet:v:254:y:2025:i:c:s0165176525002411. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.