|
EconStor >
Goethe-Universität Frankfurt am Main >
Center for Financial Studies (CFS), Universität Frankfurt a. M. >
CFS Working Paper Series, Universität Frankfurt a. M. >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/10419/43278
|
| | |
| Title: | | Price adjustment to news with uncertain precision  |
| Authors: | | Hautsch, Nikolaus Hess, Dieter E. Müller, Christoph |
| Issue Date: | | 2008 |
| Series/Report no.: | | CFS Working Paper 2008/28 |
| Abstract: | | Bayesian learning provides the core concept of processing noisy information. In standard Bayesian frameworks, assessing the price impact of information requires perfect knowledge of news' precision. In practice, however, precision is rarely dis- closed. Therefore, we extend standard Bayesian learning, suggesting traders infer news' precision from magnitudes of surprises and from external sources. We show that interactions of the different precision signals may result in highly nonlinear price responses. Empirical tests based on intra-day T-bond futures price reactions to employment releases confirm the model's predictions and show that the effects are statistically and economically significant. |
| Subjects: | | Bayesian Learning Macroeconomic Announcements Information Quality Precision Signals |
| JEL: | | E44 G14 |
| Document Type: | | Working Paper |
| Appears in Collections: | | CFS Working Paper Series, Universität Frankfurt a. M.
|
| |
| | |
Download bibliographical data as:
BibTeX
|
| |
Share on:http://hdl.handle.net/10419/43278
|
Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.
|