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Price Adjustment to News with Uncertain Precision

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Author Info
Nikolaus Hautsch
Dieter Hess
Christoph Müller

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Abstract

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.

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Publisher Info
Paper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2008-025.

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Length: 47 pages
Date of creation: Mar 2008
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Handle: RePEc:hum:wpaper:sfb649dp2008-025

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

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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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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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    Other versions:
  2. Nikolaus Hautsch & Dieter Hess, 2002. "The processing of non-anticipated information in financial markets: Analyzing the impact of surprises in the employment report," CoFE Discussion Paper 02-06, Center of Finance and Econometrics, University of Konstanz. [Downloadable!]
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    Other versions:
  4. Ottaviani, Marco & Sorensen, Peter Norman, 2006. "The strategy of professional forecasting," Journal of Financial Economics, Elsevier, vol. 81(2), pages 441-466, August. [Downloadable!] (restricted)
    Other versions:
  5. Ray-Bing Chen & Meihui Guo & Wolfgang Härdle & Shih-Feng Huang, 2008. "Independent Component Analysis Via Copula Techniques," SFB 649 Discussion Papers SFB649DP2008-004, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
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  9. Silke Hüttel & Oliver Mußhoff & Martin Odening & Nataliya Zinych, 2008. "Estimating Investment Equations in Imperfect Capital Markets," SFB 649 Discussion Papers SFB649DP2008-016, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
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  12. Rainer Schulz & Markus Staiber & Martin Wersing & Axel Werwatz, 2008. "The Accuracy of Long-term Real Estate Valuations," SFB 649 Discussion Papers SFB649DP2008-019, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Enzo Giacomini & Wolfgang Härdle & Volker Krätschmer, 2008. "Dynamic Semiparametric Factor Models in Risk Neutral Density Estimation," SFB 649 Discussion Papers SFB649DP2008-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
  2. Viktor Winschel & Markus Krätzig, 2008. "JBendge: An Object-Oriented System for Solving, Estimating and Selecting Nonlinear Dynamic Models," SFB 649 Discussion Papers SFB649DP2008-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
  3. George J. Jiang & Ingrid Lo & Adrien Verdelhan, 2008. "Information Shocks, Jumps, and Price Discovery -- Evidence from the U.S. Treasury Market," Working Papers 08-22, Bank of Canada. [Downloadable!]
  4. Anton Andriyashin, 2008. "Stock Picking via Nonsymmetrically Pruned Binary Decision Trees," SFB 649 Discussion Papers SFB649DP2008-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
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