IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2609.38545.html

Say, Echo, Do: Strategic Narratives and Revealed Positioning in Financial Markets

Author

Listed:
  • Ali Atiah Alzahrani

Abstract

Machine-learning signals built from financial text treat what institutions say, and what the media repeat, as evidence about value. But whoever shapes a narrative may be trading against it. We study markets with three observable voices: institutional statements (Say), media repetition (Echo) and revealed positioning (Do). We ask when words should be followed and when they should be faded. In a linear-quadratic model of an informed institution that speaks and trades before a partly credulous crowd, talking an asset down while buying it is optimal exactly when $\varphi^2

Suggested Citation

  • Ali Atiah Alzahrani, 2026. "Say, Echo, Do: Strategic Narratives and Revealed Positioning in Financial Markets," Papers 2609.38545, arXiv.org.
    • Handle: RePEc:arx:papers:2609.38545
    as

    Download full text from publisher

    File URL: https://arxiv.org/pdf/2609.38545
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. George William Evans, 2001. "Expectations in Macroeconomics Adaptive versus Eductive Learning," Revue économique, Presses de Sciences-Po, vol. 52(3), pages 573-582.
    2. Guillermo Llorente & Roni Michaely & Gideon Saar & Jiang Wang, 2002. "Dynamic Volume-Return Relation of Individual Stocks," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1005-1047.
    3. Shimon Kogan & Tobias J Moskowitz & Marina Niessner, 2023. "Social Media and Financial News Manipulation," Review of Finance, European Finance Association, vol. 27(4), pages 1229-1268.
    4. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    5. Zheng Tracy Ke & Bryan T. Kelly & Dacheng Xiu, 2019. "Predicting Returns With Text Data," NBER Working Papers 26186, National Bureau of Economic Research, Inc.
    6. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    7. Paul Glasserman & Caden Lin, 2023. "Assessing Look-Ahead Bias in Stock Return Predictions Generated By GPT Sentiment Analysis," Papers 2309.17322, arXiv.org.
    8. Kartik, Navin & Ottaviani, Marco & Squintani, Francesco, 2007. "Credulity, lies, and costly talk," Journal of Economic Theory, Elsevier, vol. 134(1), pages 93-116, May.
    9. Merton, Robert C, 1969. "Lifetime Portfolio Selection under Uncertainty: The Continuous-Time Case," The Review of Economics and Statistics, MIT Press, vol. 51(3), pages 247-257, August.
    10. Charles R. Harris & K. Jarrod Millman & Stéfan J. Walt & Ralf Gommers & Pauli Virtanen & David Cournapeau & Eric Wieser & Julian Taylor & Sebastian Berg & Nathaniel J. Smith & Robert Kern & Matti Picu, 2020. "Array programming with NumPy," Nature, Nature, vol. 585(7825), pages 357-362, September.
    11. Crawford, Vincent P & Sobel, Joel, 1982. "Strategic Information Transmission," Econometrica, Econometric Society, vol. 50(6), pages 1431-1451, November.
    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. Singh, Hargungeet, 2026. "Dynamic communication with trading commissions," Journal of Mathematical Economics, Elsevier, vol. 122(C).
    2. Junyu Chen & Tom Boot & Lingwei Kong & Weining Wang, 2026. "Transformer-based CoVaR: Systemic Risk in Textual Information," Papers 2602.12490, arXiv.org.
    3. Oleg Chuprinin & Massimo Massa & Bastian von Beschwitz, 2015. "Why Do Short Sellers Like Qualitative News?," International Finance Discussion Papers 1149, Board of Governors of the Federal Reserve System (U.S.).
    4. von Beschwitz, Bastian & Chuprinin, Oleg & Massa, Massimo, 2017. "Why Do Short Sellers Like Qualitative News?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(2), pages 645-675, April.
    5. Feri, Francesco & Meléndez-Jiménez, Miguel A. & Ponti, Giovanni & Vega-Redondo, Fernando & Yu, Haihan, 2020. "Pooling or fooling? An experiment on signaling," Journal of Economic Behavior & Organization, Elsevier, vol. 176(C), pages 582-596.
    6. Songrun He & Linying Lv & Asaf Manela & Jimmy Wu, 2025. "Chronologically Consistent Large Language Models," Papers 2502.21206, arXiv.org, revised Jul 2025.
    7. Joel Peress & Daniel Schmidt, 2020. "Glued to the TV: Distracted Noise Traders and Stock Market Liquidity," Journal of Finance, American Finance Association, vol. 75(2), pages 1083-1133, April.
    8. Persson, Petra, 2018. "Attention manipulation and information overload," Behavioural Public Policy, Cambridge University Press, vol. 2(1), pages 78-106, May.
    9. Johannes Abeler & Armin Falk & Fabian Kosse, 2025. "Malleability of Preferences for Honesty," The Economic Journal, Royal Economic Society, vol. 135(667), pages 982-998.
    10. Yue Zhao & Difang Wan, 2018. "Institutional high frequency trading and price discovery: Evidence from an emerging commodity futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(2), pages 243-270, February.
    11. Hau, Liya & Zhu, Huiming & Shahbaz, Muhammad & Sun, Wuqin, 2021. "Does transaction activity predict Bitcoin returns? Evidence from quantile-on-quantile analysis," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    12. Anita Todea, 2018. "Culture And Stock Price Reaction To Private Information," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 21, pages 117-130, June.
    13. Shuo Liu & Dimitri Migrow, 2019. "Designing organizations in volatile markets," ECON - Working Papers 319, Department of Economics - University of Zurich.
    14. John L. Campbell & Hsinchun Chen & Dan S. Dhaliwal & Hsin-min Lu & Logan B. Steele, 2014. "The information content of mandatory risk factor disclosures in corporate filings," Review of Accounting Studies, Springer, vol. 19(1), pages 396-455, March.
    15. Jorge M. Streb & Gustavo Torrens, 2011. "Meaningful talk," CEMA Working Papers: Serie Documentos de Trabajo. 443, Universidad del CEMA, revised May 2017.
    16. Ivan Balbuzanov, 2019. "Lies and consequences," International Journal of Game Theory, Springer;Game Theory Society, vol. 48(4), pages 1203-1240, December.
    17. Gabriel Desgranges & Celine Rochon, 2008. "Conformism, Public News and Market Effciency," OFRC Working Papers Series 2008fe16, Oxford Financial Research Centre.
    18. Gordon Rausser & Leo Simon & Jinhua Zhao, 2015. "Rational exaggeration and counter-exaggeration in information aggregation games," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 59(1), pages 109-146, May.
    19. Lai, Ernest K., 2014. "Expert advice for amateurs," Journal of Economic Behavior & Organization, Elsevier, vol. 103(C), pages 1-16.
    20. Jakusch, Sven Thorsten, 2017. "On the applicability of maximum likelihood methods: From experimental to financial data," SAFE Working Paper Series 148, Leibniz Institute for Financial Research SAFE, revised 2017.

    More about this item

    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:arx:papers:2609.38545. 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: arXiv administrators (email available below). General contact details of provider: https://arxiv.org/ .

    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.