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    This article has been cited by the following publications. This list is generated based on data provided by CrossRef.
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    Laidroo, Laivi 2011. Market Liquidity and Public Announcements' Disclosure Quality on Tallinn, Riga, and Vilnius Stock Exchanges. Emerging Markets Finance and Trade, Vol. 47, Issue. 0, p. 54.
    Brevik, Frode and d’Addona, Stefano 2010. Information Quality and Stock Returns Revisited. Journal of Financial and Quantitative Analysis, Vol. 45, Issue. 06, p. 1419.
    Pastor, Lubos and Veronesi, Pietro 2009. Learning in Financial Markets. Annual Review of Financial Economics, Vol. 1, Issue. 1, p. 361.
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    Vanden, Joel M. 2008. Information Quality and Options. Review of Financial Studies, Vol. 21, Issue. 6, p. 2635.
    WARREN, GEOFFREY J. 2008. Implications for Asset Pricing Puzzles of a Roll-over Assumption for the Risk-Free Asset*. International Review of Finance, Vol. 8, Issue. 3-4, p. 125.
    Li, Ming-Yi and Hui, Xiao-Feng 2007. Regulation Fair Disclosure's Effects on the Cost of Capital: Financial Innovation or Policy Failure. p. 3914.
    Feldman, David 2007. Incomplete information equilibria: Separation theorems and other myths. Annals of Operations Research, Vol. 151, Issue. 1, p. 119.
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Information Quality, Learning, and Stock Market Returns

  • George Li (a1)
Abstract

This paper studies how the precision of noisy public information that investors receive about the expected aggregate dividend growth rate affects stock market returns. I show that less precise information can increase the risk premium and stock return volatility. The numerical results from my calibrated model also show that noisy information can significantly increase the risk premium and stock return volatility. My finding implies that the presence of noisy information may help explain the large average risk premium and return volatility in the U.S. financial market. In addition, my finding suggests it is optimal for firms to disclose to investors more precise information to reduce the cost of equity capital.

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COPYRIGHT: © School of Business Administration, University of Washington 2005
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Journal of Financial and Quantitative Analysis
  • ISSN: 0022-1090
  • EISSN: 1756-6916
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