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Inferring Information Frequency and Quality

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  • John Owens
  • Douglas G. Steigerwald

Abstract

We develop a microstructure model that, in contrast to previous models, allows one to estimate the frequency and quality of private information. In addition, the model produces stationary asset price and trading volume series. We find evidence that information arrives frequently within a day and that this information is of high quality. The frequent arrival of information, while in contrast to previous microstructure model estimates, accords with nonmodel-based estimates and the related literature testing the mixture-of-distributions hypothesis. To determine if the estimates are correctly reflecting the arrival of latent information, we estimate the parameters over half-hour intervals within the day. Comparison of the parameter estimates with measures of persistent price changes reveals that the estimates reflect the arrival of latent information. Copyright 2005, Oxford University Press.

Suggested Citation

  • John Owens & Douglas G. Steigerwald, 2005. "Inferring Information Frequency and Quality," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 3(4), pages 500-524.
  • Handle: RePEc:oup:jfinec:v:3:y:2005:i:4:p:500-524
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbi024
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    References listed on IDEAS

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    Cited by:

    1. Francis X. Diebold & Georg Strasser, 2013. "On the Correlation Structure of Microstructure Noise: A Financial Economic Approach," Review of Economic Studies, Oxford University Press, vol. 80(4), pages 1304-1337.
    2. Kitamura, Yoshihiro, 2016. "The probability of informed trading measured with price impact, price reversal, and volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 42(C), pages 77-90.
    3. Francis X. Diebold & Georg H. Strasser, 2008. "On the Correlation Structure of Microstructure Noise in Theory and Practice," PIER Working Paper Archive 08-038, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    4. Kelly David L. & Steigerwald Douglas G, 2004. "Private Information and High-Frequency Stochastic Volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(1), pages 1-30, March.
    5. Lim, Bryan Y., 2011. "Short-sale constraints and price bubbles," Journal of Banking & Finance, Elsevier, vol. 35(9), pages 2443-2453, September.
    6. Wang, Jianxin & Yang, Minxian, 2015. "How well does the weighted price contribution measure price discovery?," Journal of Economic Dynamics and Control, Elsevier, vol. 55(C), pages 113-129.

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