Arbeitspapier
Bayesian learning in financial markets: Testing for the relevance of information precision in price discovery
An important claim of Bayesian learning and a standard assumption in price discovery models is that the strength of the price impact of unanticipated information depends on the precision of the news. In this paper, we test for this assumption by analyzing intra-day price responses of CBOT T-bond futures to U.S. employment announcements. By employing additional detail information besides the widely used headline figures, we extract release-specific precision measures which allow to test for the claim of Bayesian updating. We find that the price impact of more precise information is significantly stronger. The results remain stable even after controlling for an asymmetric price response to 'good' and 'bad' news.
- Sprache
-
Englisch
- Erschienen in
-
Series: CFR Working Paper ; No. 04-10
- Klassifikation
-
Wirtschaft
Financial Markets and the Macroeconomy
Information and Market Efficiency; Event Studies; Insider Trading
- Thema
-
Bayesian learning
information precision
macroeconomic announcements
asymmetric price response
financial markets
high-frequency data
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Hautsch, Nikolaus
Hess, Dieter
- Ereignis
-
Veröffentlichung
- (wer)
-
University of Cologne, Centre for Financial Research (CFR)
- (wo)
-
Cologne
- (wann)
-
2004
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Hautsch, Nikolaus
- Hess, Dieter
- University of Cologne, Centre for Financial Research (CFR)
Entstanden
- 2004
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