IDEAS home Printed from https://ideas.repec.org/a/taf/hbhfxx/v20y2019i1p31-41.html
   My bibliography  Save this article

News Sentiment: A New Yield Curve Factor

Author

Listed:
  • Nina Gotthelf
  • Matthias W. Uhl

Abstract

The authors show that sentiments from newspaper articles can explain and predict movements in the term structure of U.S. government bonds. This effect is stronger at the short end of the curve, coinciding with greater volatility and investors' need to continually reassess the Fed's reaction function. Facing such uncertainty, market participants rely on news and sentiment as a central element in their decision-making process. Considering this dependence, the authors propose a new yield curve factor—news sentiment—that is distinct from the 3 established yield curve factors (level, slope, and curvature) as well as from fundamental macroeconomic variables.

Suggested Citation

  • Nina Gotthelf & Matthias W. Uhl, 2019. "News Sentiment: A New Yield Curve Factor," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 20(1), pages 31-41, January.
  • Handle: RePEc:taf:hbhfxx:v:20:y:2019:i:1:p:31-41
    DOI: 10.1080/15427560.2018.1432620
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/15427560.2018.1432620
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/15427560.2018.1432620?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 search for a different version of it.

    Citations

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


    Cited by:

    1. Eugster, Patrick & Uhl, Matthias W., 2024. "Forecasting inflation using sentiment," Economics Letters, Elsevier, vol. 236(C).
    2. Banerjee, Ameet Kumar & Dionisio, Andreia & Pradhan, H.K. & Mahapatra, Biplab, 2021. "Hunting the quicksilver: Using textual news and causality analysis to predict market volatility," International Review of Financial Analysis, Elsevier, vol. 77(C).
    3. Yang, Ann Shawing, 2020. "Misinformation corrections of corporate news: Corporate clarification announcements," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    4. Aneeta Elsa Simon & Manu K.S., 2023. "Does Sentiments Impact the Returns of Commodity Derivatives? An Evidence from Multi-commodity Exchange India," Vision, , vol. 27(1), pages 79-92, February.
    5. Mohammad Alomari & Abdel Razzaq Al rababa’a & Ghaith El-Nader & Ahmad Alkhataybeh, 2021. "Who’s behind the wheel? The role of social and media news in driving the stock–bond correlation," Review of Quantitative Finance and Accounting, Springer, vol. 57(3), pages 959-1007, October.
    6. Durand, Robert B. & Khuu, Joyce & Smales, Lee A., 2023. "Lost in translation. When sentiment metrics for one market are derived from two different languages," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    7. Audrino, Francesco & Offner, Eric A., 2024. "The impact of macroeconomic news sentiment on interest rates," International Review of Financial Analysis, Elsevier, vol. 94(C).

    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:taf:hbhfxx:v:20:y:2019:i:1:p:31-41. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/hbhf .

    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.