Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/70120
Authors: 
Hautsch, Nikolaus
Hess, Dieter
Müller, Christoph
Year of Publication: 
2011
Series/Report no.: 
CFR Working Paper 08-04 [rev.]
Abstract: 
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.
Subjects: 
Bayesian learning
macroeconomic announcements
information quality
precision signals
JEL: 
E44
G14
Document Type: 
Working Paper

Files in This Item:
File
Size
487.22 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.