An improved estimation method and empirical properties of the probability of informed trading

Yuxing Yan, Shaojun Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

47 Citations (Scopus)


We report evidence that boundary solutions can cause a bias in the estimate of the probability of informed trading (PIN). We develop an algorithm to overcome this bias and use it to estimate PIN for nearly 80,000 stock-quarters between 1993 and 2004. We obtain two sets of PIN estimates by using the factorized likelihood functions in both Easley, Hvidkjaer, and O'Hara (EHO, 2010) and Lin and Ke (LK, 2011), respectively. We find that the estimate based on the EHO factorization is systematically smaller than the estimate based on the LK factorization, meaning that there is a downward bias associated with the EHO factorization. In addition, we find that boundary solutions appear with a very high frequency when the LK factorization is used. Thus it is necessary to use the LK factorization together with the algorithm in this paper. At last, we document several interesting empirical properties of PIN.
Original languageEnglish
Pages (from-to)454-467
Number of pages14
JournalJournal of Banking and Finance
Issue number2
Publication statusPublished - 1 Feb 2012


  • Boundary solution
  • PIN
  • Probability of informed trading

ASJC Scopus subject areas

  • Finance
  • Economics and Econometrics

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