IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/28749.html
   My bibliography  Save this paper

Using Social Media to Identify the Effects of Congressional Viewpoints on Asset Prices

Author

Listed:
  • Francesco Bianchi
  • Roberto Gomez Cram
  • Howard Kung

Abstract

We use a high-frequency identification approach to document that individual politicians affect asset prices. We exploit the regular flow of viewpoints contained in Congress members’ tweets. Supportive (critical) tweets increase (decrease) the stock prices of the targeted firm and the corresponding industry in minutes around the tweet. The bulk of the stock price effects is concentrated in the tweets revealing news about future legislative action. The effects are amplified around committee meeting days, especially when the tweet originates from committee members and influential politicians. Overall, we show that Congress members’ social media accounts are an important source of political news.

Suggested Citation

  • Francesco Bianchi & Roberto Gomez Cram & Howard Kung, 2021. "Using Social Media to Identify the Effects of Congressional Viewpoints on Asset Prices," NBER Working Papers 28749, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:28749
    Note: AP EFG ME
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w28749.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bianchi, Francesco & Gómez-Cram, Roberto & Kind, Thilo & Kung, Howard, 2023. "Threats to central bank independence: High-frequency identification with twitter," Journal of Monetary Economics, Elsevier, vol. 135(C), pages 37-54.
    2. Javier Gil-Bazo & Juan F. Imbet, 2022. "Tweeting for money: Social media and mutual fund flows," Economics Working Papers 1846, Department of Economics and Business, Universitat Pompeu Fabra.
    3. Guy Aridor & Rafael Jiménez-Durán & Ro'ee Levy & Lena Song, 2024. "The Economics of Social Media," Journal of Economic Literature, American Economic Association, vol. 62(4), pages 1422-1474, December.
    4. Juan Imbet & J. Anthony Cookson & Corbin Fox & Christoph Schiller & Javier Gil-Bazo, 2024. "Social Media as a Bank Run Catalyst," Post-Print hal-04660083, HAL.
    5. Sui, Cong & Wang, Shuhan & Zheng, Wei, 2024. "Sentiment as a shipping market predictor: Testing market-specific language models," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 189(C).
    6. Bales, Stephan & Burghof, Hans-Peter, 2024. "Public attention, sentiment and the default of Silicon Valley Bank," The North American Journal of Economics and Finance, Elsevier, vol. 69(PA).
    7. Marco Grotteria & Max Miller & S.Lakshmi Naaraayanan, 2024. "Foreign influence in US politics," Discussion Papers 2024-12, Nottingham Interdisciplinary Centre for Economic and Political Research (NICEP).
    8. Arteaga-Garavito, Maria Jose & Croce, Mariano M. & Farroni, Paolo & Wolfskeil, Isabella, 2024. "When the markets get CO.V.I.D: COntagion, Viruses, and Information Diffusion," Journal of Financial Economics, Elsevier, vol. 157(C).
    9. Cookson, J. Anthony & Lu, Runjing & Mullins, William & Niessner, Marina, 2024. "The social signal," Journal of Financial Economics, Elsevier, vol. 158(C).
    10. Alistair Macaulay & Wenting Song, 2022. "Narrative-Driven Fluctuations in Sentiment: Evidence Linking Traditional and Social Media," Economics Series Working Papers 973, University of Oxford, Department of Economics.

    More about this item

    JEL classification:

    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:nbr:nberwo:28749. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    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.