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News Sentiment: A New Yield Curve Factor


Gotthelf, Nina; Uhl, Matthias W (2019). News Sentiment: A New Yield Curve Factor. Journal of Behavioral Finance, 20(1):21-31.

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.

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.

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11 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Banking and Finance
Dewey Decimal Classification:330 Economics
Scopus Subject Areas:Social Sciences & Humanities > Experimental and Cognitive Psychology
Social Sciences & Humanities > Finance
Language:English
Date:1 March 2019
Deposited On:17 May 2019 13:48
Last Modified:22 Sep 2023 01:41
Publisher:Taylor & Francis
ISSN:1542-7560
OA Status:Closed
Publisher DOI:https://doi.org/10.1080/15427560.2018.1432620
Related URLs:https://www.tandfonline.com/doi/abs/10.1080/15427560.2018.1432620 (Publisher)
Other Identification Number:merlin-id:16277
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