Resource title

Price adjustment to news with uncertain precision

Resource image

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Resource description

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

Resource author

Nikolaus Hautsch, Dieter E. Hess, Christoph Müller

Resource publisher

Resource publish date

Resource language

eng

Resource content type

text/html

Resource resource URL

http://hdl.handle.net/10419/25267

Resource license

Adapt according to the presented license agreement and reference the original author.