Price adjustment to news with uncertain precision

Arbeitspapier

We analyze how markets adjust to new information when the reliability of news is uncertain and has to be estimated itself. We propose a Bayesian learning model where market participants receive fundamental information along with noisy estimates of news' precision. It is shown that the efficiency of a precision estimate drives the the slope and the shape of price response functions to news. Increasing estimation errors induce stronger nonlinearities in price responses. Analyzing high-frequency reactions of Treasury bond futures prices to employment releases, we find strong empirical support for the model's predictions and show that the consideration of precision uncertainty is statistically and economically important.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: CFR Working Paper ; No. 08-04 [rev.]

Classification and Topics

• Classification: Wirtschaft ; Financial Markets and the Macroeconomy ; Information and Market Efficiency; Event Studies; Insider Trading
• Subject: Bayesian learning ; macroeconomic announcements ; information quality ; precision signals

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Hautsch, Nikolaus ; Hess, Dieter ; Müller, Christoph
• Event: Veröffentlichung
• (who): University of Cologne, Centre for Financial Research (CFR)
• (where): Cologne
• (when): 2011

Further information

• Handle: http://hdl.handle.net/10419/70120
• Last update: 10.03.2025, 11:42 AM CET