IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2410.20214.html
   My bibliography  Save this paper

Strategic Control of Facial Expressions by the Fed Chair

Author

Listed:
  • Hunter Ng

Abstract

This article investigates whether the Federal Reserve Chair strategically controls facial expressions during FOMC press conferences and how these nonverbal cues affect financial markets. I use facial recognition technology on videos of press conferences from April 2011 to December 2020 to quantify changes in the Chair's nonverbal signals. Results show that facial expressions serve as a separate public signal, distinct from verbal content. Using deepfakes, I find that the same facial expressions expressed by different Fed Chairs are interpreted differentially. As their tenure increases, negative expressions become more frequent, eliciting adverse market reactions. Furthermore, the markets interpretation of these expressions evolves over time, suggesting that investors process facial cues with dual-processing finite-state Markov memory. In line with the Fed's goals of transparency and non-volatility, I find that Fed Chairs do not strategically control their expressions.

Suggested Citation

  • Hunter Ng, 2024. "Strategic Control of Facial Expressions by the Fed Chair," Papers 2410.20214, arXiv.org.
  • Handle: RePEc:arx:papers:2410.20214
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2410.20214
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sean Cao Robert H. Smith & Wei Jiang & Baozhong Yang J. Mack Robinson & Alan L Zhang & Tarun Ramadorai, 2023. "How to Talk When a Machine Is Listening: Corporate Disclosure in the Age of AI," The Review of Financial Studies, Society for Financial Studies, vol. 36(9), pages 3603-3642.
    2. Alexopoulos, Michelle & Han, Xinfen & Kryvtsov, Oleksiy & Zhang, Xu, 2024. "More than words: Fed Chairs’ communication during congressional testimonies," Journal of Monetary Economics, Elsevier, vol. 142(C).
    3. Boguth, Oliver & Grégoire, Vincent & Martineau, Charles, 2019. "Shaping Expectations and Coordinating Attention: The Unintended Consequences of FOMC Press Conferences," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(6), pages 2327-2353, December.
    4. Snehal Banerjee & Ron Kaniel & Ilan Kremer, 2009. "Price Drift as an Outcome of Differences in Higher-Order Beliefs," The Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3707-3734, September.
    5. Blankespoor, Elizabeth & deHaan, Ed & Marinovic, Iván, 2020. "Disclosure processing costs, investors’ information choice, and equity market outcomes: A review," Journal of Accounting and Economics, Elsevier, vol. 70(2).
    6. Emi Nakamura & Jón Steinsson, 2018. "High-Frequency Identification of Monetary Non-Neutrality: The Information Effect," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(3), pages 1283-1330.
    7. Neuhierl, Andreas & Weber, Michael, 2019. "Monetary policy communication, policy slope, and the stock market," Journal of Monetary Economics, Elsevier, vol. 108(C), pages 140-155.
    8. Amengual, Dante & Xiu, Dacheng, 2018. "Resolution of policy uncertainty and sudden declines in volatility," Journal of Econometrics, Elsevier, vol. 203(2), pages 297-315.
    9. Stephen Morris & Hyun Song Shin, 2002. "Social Value of Public Information," American Economic Review, American Economic Association, vol. 92(5), pages 1521-1534, December.
    10. Jeremy C. Stein & Adi Sunderam, 2018. "The Fed, the Bond Market, and Gradualism in Monetary Policy," Journal of Finance, American Finance Association, vol. 73(3), pages 1015-1060, June.
    11. Franklin Allen & Stephen Morris & Hyun Song Shin, 2006. "Beauty Contests and Iterated Expectations in Asset Markets," The Review of Financial Studies, Society for Financial Studies, vol. 19(3), pages 719-752.
    12. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
    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. Zhao Han & Xiaohan Ma & Ruoyun Mao, 2023. "The Role of Dispersed Information in Inflation and Inflation Expectations," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 48, pages 72-106, April.
    2. Xavier Vives & Giovanni Cespa, 2011. "Higher Order Expectations, Illiquidity, and Short Term Trading," 2011 Meeting Papers 929, Society for Economic Dynamics.
    3. Giovanni Cespa & Xavier Vives, 2011. "Expectations, Liquidity, and Short-term Trading," CESifo Working Paper Series 3390, CESifo.
    4. Liu, Hong & Tang, Xiaoxiao & Zhou, Guofu, 2022. "Recovering the FOMC risk premium," Journal of Financial Economics, Elsevier, vol. 145(1), pages 45-68.
    5. Paritosh Chandra Sinha, 2023. "Attention to the Fads and Fashions in the Indian Stock Markets During COVID-19," Vision, , vol. 27(2), pages 202-224, April.
    6. Guido Lorenzoni, 2009. "A Theory of Demand Shocks," American Economic Review, American Economic Association, vol. 99(5), pages 2050-2084, December.
    7. Gómez-Cram, Roberto & Grotteria, Marco, 2022. "Real-time price discovery via verbal communication: Method and application to Fedspeak," Journal of Financial Economics, Elsevier, vol. 143(3), pages 993-1025.
    8. Angeletos, G.-M. & Lian, C., 2016. "Incomplete Information in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 1065-1240, Elsevier.
    9. Jia, Chengcheng, 2023. "The informational effect of monetary policy and the case for policy commitment," European Economic Review, Elsevier, vol. 156(C).
    10. Kroencke, Tim A. & Schmeling, Maik & Schrimpf, Andreas, 2021. "The FOMC Risk Shift," Journal of Monetary Economics, Elsevier, vol. 120(C), pages 21-39.
    11. Armelius, Hanna & Bertsch, Christoph & Hull, Isaiah & Zhang, Xin, 2020. "Spread the Word: International spillovers from central bank communication," Journal of International Money and Finance, Elsevier, vol. 103(C).
    12. Angeletos, George-Marios & La’O, Jennifer, 2009. "Incomplete information, higher-order beliefs and price inertia," Journal of Monetary Economics, Elsevier, vol. 56(S), pages 19-37.
    13. Yang, Chunpeng & Cai, Chuangqun, 2014. "Higher order expectations in sentiment asset pricing model," Economic Modelling, Elsevier, vol. 39(C), pages 95-100.
    14. Luz, Valentin & Schauer, Victor & Viehweger, Martin, 2024. "Beyond preferences: Beliefs in sustainable investing," Journal of Economic Behavior & Organization, Elsevier, vol. 220(C), pages 584-607.
    15. Dan Zhu & Qingwei Wang & John Goddard, 2022. "A new hedging hypothesis regarding prediction interval formation in stock price forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 697-717, July.
    16. George-Marios Angeletos & Chen Lian, 2018. "Forward Guidance without Common Knowledge," American Economic Review, American Economic Association, vol. 108(9), pages 2477-2512, September.
    17. Ichiro Fukunaga, 2007. "Imperfect Common Knowledge, Staggered Price Setting, and the Effects of Monetary Policy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1711-1739, October.
    18. Camille Cornand & Frank Heinemann, 2015. "Macro-expérimentation autour des fonctions des banques centrales," Revue française d'économie, Presses de Sciences-Po, vol. 0(2), pages 3-47.
    19. Romain Baeriswyl & Camille Cornand, 2014. "Reducing Overreaction To Central Banks' Disclosures: Theory And Experiment," Journal of the European Economic Association, European Economic Association, vol. 12(4), pages 1087-1126, August.
    20. Kurz, Mordecai, 2008. "Beauty contests under private information and diverse beliefs: How different?," Journal of Mathematical Economics, Elsevier, vol. 44(7-8), pages 762-784, July.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:2410.20214. 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: http://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.