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Bayesian Learning in Financial Markets - Testing for the Relevance of Information Precision in Price Discovery

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Author Info
Nikolaus Hautsch (Institute of Economics, University of Copenhagen)
Dieter Hess (University of Cologne)

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Abstract

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.

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Publisher Info
Paper provided by University of Copenhagen. Department of Economics in its series Discussion Papers with number 04-17.

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Length: 25 pages
Date of creation: Sep 2004
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Handle: RePEc:kud:kuiedp:0417

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Related research
Keywords: Bayesian learning; information precision; macroeconomic announcements; asymmetric price response; financial markets; high-frequency data;

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Find related papers by JEL classification:
E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies

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  1. Menkhoff, Lukas & Schmeling, Maik, 2007. "Whose trades convey information? Evidence from a cross-section of traders," Diskussionspapiere der Wirtschaftswissenschaftlichen Fakultät der Universität Hannover dp-357, Universität Hannover, Wirtschaftswissenschaftliche Fakultät. [Downloadable!]
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This page was last updated on 2009-11-16.

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