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Price adjustment to news with uncertain precision

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  • Hautsch, Nikolaus
  • Hess, Dieter
  • Müller, Christoph

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. --

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Bibliographic Info

Paper provided by University of Cologne, Centre for Financial Research (CFR) in its series CFR Working Papers with number 08-04 [rev.].

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Date of creation: 2011
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Handle: RePEc:zbw:cfrwps:0804r

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Keywords: Bayesian learning; macroeconomic announcements; information quality; precision signals;

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Cited by:
  1. Hautsch, Nikolaus & Hess, Dieter & Veredas, David, 2011. "The impact of macroeconomic news on quote adjustments, noise, and informational volatility," Journal of Banking & Finance, Elsevier, Elsevier, vol. 35(10), pages 2733-2746, October.
  2. Hess, Dieter & Orbe, Sebastian, 2011. "Irrationality or efficiency of macroeconomic survey forecasts? Implications from the anchoring bias test," CFR Working Papers 11-13, University of Cologne, Centre for Financial Research (CFR).

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