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A computing bias in estimating the probability of informed trading

Author

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

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.

Suggested Citation

  • William Lin, Hsiou-Wei & Ke, Wen-Chyan, 2011. "A computing bias in estimating the probability of informed trading," Journal of Financial Markets, Elsevier, vol. 14(4), pages 625-640, November.
  • Handle: RePEc:eee:finmar:v:14:y:2011:i:4:p:625-640
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    References listed on IDEAS

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    1. Duarte, Jefferson & Young, Lance, 2009. "Why is PIN priced?," Journal of Financial Economics, Elsevier, vol. 91(2), pages 119-138, February.
    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. Boehmer, Ekkehart & Grammig, Joachim & Theissen, Erik, 2007. "Estimating the probability of informed trading--does trade misclassification matter?," Journal of Financial Markets, Elsevier, vol. 10(1), pages 26-47, February.
    4. 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.
    5. 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.
    6. Easley, David, et al, 1996. " Liquidity, Information, and Infrequently Traded Stocks," Journal of Finance, American Finance Association, vol. 51(4), pages 1405-1436, September.
    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 733-746, June.
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    Citations

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    Cited by:

    1. 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.
    2. Ersan, Oguz & Alıcı, Aslı, 2016. "An unbiased computation methodology for estimating the probability of informed trading (PIN)," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 43(C), pages 74-94.
    3. 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.
    4. 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.
    5. Paiardini, Paola, 2015. "Informed trading in parallel bond markets," Journal of Financial Markets, Elsevier, vol. 26(C), pages 103-121.
    6. Jackson, David, 2013. "Estimating PIN for firms with high levels of trading," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 116-120.
    7. 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.
    8. Thomas Pöppe & Michael Aitken & Dirk Schiereck & Ingo Wiegand, 2016. "A PIN per day shows what news convey: the intraday probability of informed trading," Review of Quantitative Finance and Accounting, Springer, vol. 47(4), pages 1187-1220, November.
    9. Chen, Yifan & Zhao, Huainan, 2012. "Informed trading, information uncertainty, and price momentum," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2095-2109.
    10. Kim, Sangwan & Lim, Steve C., 2017. "Earnings comparability and informed trading," Finance Research Letters, Elsevier, vol. 20(C), pages 130-136.
    11. 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.
    12. Petchey, James & Wee, Marvin & Yang, Joey, 2016. "Pinning down an effective measure for probability of informed trading," Pacific-Basin Finance Journal, Elsevier, vol. 40(PB), pages 456-475.
    13. Moonsoo Kang & Kiseok Nam, 2015. "Informed trade and idiosyncratic return variation," Review of Quantitative Finance and Accounting, Springer, vol. 44(3), pages 551-572, April.
    14. Ke, Wen-Chyan & Chen, Hueiling & Lin, Hsiou-Wei W. & Liu, Yo-Chia, 2017. "The impact of numerical superstition on the final digit of stock price," The North American Journal of Economics and Finance, Elsevier, vol. 39(C), pages 145-157.

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