Price adjustment to news with uncertain precision

Arbeitspapier

Bayesian learning provides a core concept of information processing in financial markets. Typically it is assumed that market participants perfectly know the quality of released news. However, in practice, news' precision is rarely disclosed. Therefore, we extend standard Bayesian learning allowing traders to infer news' precision from two different sources. If information is perceived to be imprecise, prices react stronger. Moreover, interactions of the different precision signals affect price responses nonlinearly. Empirical tests based on intra-day T-bond futures price reactions to employment releases confirm the model's predictions and reveal statistically and economically significant effects of news' precision. Keywords: Bayesian learning ; information quality ; precision signals ; macroeconomic announcements

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: SFB 649 Discussion Paper ; No. 2008,025

Classification and Topics

• Classification: Wirtschaft ; Financial Markets and the Macroeconomy ; Information and Market Efficiency; Event Studies; Insider Trading
• Subject: Börsenkurs ; Anlageverhalten ; Informationsverhalten ; Lernprozess ; Wirtschaftsinformation ; Informationswert ; Ankündigungseffekt ; Theorie ; USA

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Hautsch, Nikolaus ; Hess, Dieter E. ; Müller, Christoph
• Event: Veröffentlichung
• (who): Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
• (where): Berlin
• (when): 2008

Further information

• Handle: http://hdl.handle.net/10419/25267
• Last update: 10.03.2025, 11:42 AM CET