Journal of Financial and Quantitative Analysis

Research Article

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

Nikolaus Hautscha1 and Dieter Hessa2

a1, Humboldt-Universität zu Berlin, Department of Economics, Spandauer Str. 1, D-10178, Berlin, Germany

a2, University of Cologne, Corporate Finance Seminar and Centre for Financial Research, Albert-Magnus-Platz, D-50923, Cologne, Germany


Bayesian learning claims that the strength of the price impact of unanticipated information depends on the relative precision of traders' prior and posterior beliefs. In this paper, we test for this implication of Bayesian models by analyzing intraday price responses of T-bond futures to U.S. employment announcements. By employing additional detailed information in addition to the widely used headline figures, we extract release-specific precision measures. We find that the price impact of more precise information is significantly stronger, even after controlling for an asymmetric price response to “good” and “bad” news. This result strengthens previous findings that differences in earnings response coefficients across companies are related to proxies for the credibility of the reported financial information.