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A computing bias in estimating the probability of informed trading

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Author Info

  • William Lin, Hsiou-Wei
  • Ke, Wen-Chyan
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    Abstract

    This study identifies a factor that leads to a bias in estimating the probability of informed trading (PIN), a widely-used microstructure measure. It is shown that, along with the numerical maximization of the likelihood function for PIN, the floating-point exception (i.e., overflow or underflow) may eliminate feasible solutions to the actual parameters in the optimization problem. Approximately 44% of PIN estimates for recent stock market data may have been subject to a downward bias that is more pronounced for active stocks than for inactive stocks. This study develops a remedy to mitigate the resulting bias.

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    File URL: http://www.sciencedirect.com/science/article/pii/S1386418111000176
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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Financial Markets.

    Volume (Year): 14 (2011)
    Issue (Month): 4 (November)
    Pages: 625-640

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    Handle: RePEc:eee:finmar:v:14:y:2011:i:4:p:625-640

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    Web page: http://www.elsevier.com/locate/finmar

    Related research

    Keywords: Floating-point exception Informed trading Market microstructure;

    References

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    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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    1. Joachim Grammig & Erik Theissen, 2002. "Estimating the Probability of Informed Trading - Does Trade Misclassification Matter?," Bonn Econ Discussion Papers bgse37_2002, University of Bonn, Germany.
    2. David Easley & Soeren Hvidkjaer & Maureen O'Hara, 2002. "Is Information Risk a Determinant of Asset Returns?," Journal of Finance, American Finance Association, vol. 57(5), pages 2185-2221, October.
    3. Grammig, Joachim & Schiereck, Dirk & Theissen, Erik, 2001. "Knowing me, knowing you: : Trader anonymity and informed trading in parallel markets," Journal of Financial Markets, Elsevier, vol. 4(4), pages 385-412, October.
    4. Easley, David, et al, 1996. " Liquidity, Information, and Infrequently Traded Stocks," Journal of Finance, American Finance Association, vol. 51(4), pages 1405-36, September.
    5. Easley, David & O'Hara, Maureen & Paperman, Joseph, 1998. "Financial analysts and information-based trade," Journal of Financial Markets, Elsevier, vol. 1(2), pages 175-201, August.
    6. Duarte, Jefferson & Young, Lance, 2009. "Why is PIN priced?," Journal of Financial Economics, Elsevier, vol. 91(2), pages 119-138, February.
    7. Lee, Charles M C & Ready, Mark J, 1991. " Inferring Trade Direction from Intraday Data," Journal of Finance, American Finance Association, vol. 46(2), pages 733-46, June.
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    Citations

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    Cited by:
    1. Yan, Yuxing & Zhang, Shaojun, 2014. "Quality of PIN estimates and the PIN-return relationship," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 137-149.
    2. Carl Chiarella & Xue-Zhong He & Lijian Wei, 2013. "Learning and Evolution of Trading Strategies in Limit Order Markets," Research Paper Series 335, Quantitative Finance Research Centre, University of Technology, Sydney.
    3. Jackson, David, 2013. "Estimating PIN for firms with high levels of trading," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 116-120.
    4. Yan, Yuxing & Zhang, Shaojun, 2012. "An improved estimation method and empirical properties of the probability of informed trading," Journal of Banking & Finance, Elsevier, vol. 36(2), pages 454-467.
    5. Sankaraguruswamy, Srinivasan & Shen, Jianfeng & Yamada, Takeshi, 2013. "The relationship between the frequency of news release and the information asymmetry: The role of uninformed trading," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4134-4143.
    6. Chen, Yifan & Zhao, Huainan, 2012. "Informed trading, information uncertainty, and price momentum," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2095-2109.

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