Estimating the probability of informed trading: A Bayesian approach

Jim Griffin, Jaideep Oberoi and Samuel D. Oduro

Journal of Banking & Finance, 2021, vol. 125, issue C

Abstract: The Probability of Informed Trading (PIN) is a widely used indicator of information asymmetry risk in the trading of securities. Its estimation using maximum likelihood algorithms has been shown to be problematic, resulting in biased or unavailable estimates, especially in the case of liquid and frequently traded assets. We provide an alternative approach to estimating PIN by means of a Bayesian method that addresses some of the shortcomings in the existing estimation strategies. The method leads to a natural quantification of the uncertainty of PIN estimates, which may prove helpful in their use and interpretation. We also provide an easy to use toolbox for estimating PIN.

Keywords: PIN; software; Bayesian estimation; information asymmetry risk; robust estimation (search for similar items in EconPapers)
JEL-codes: C13 G12 G14 (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:125:y:2021:i:c:s0378426621000030

DOI: 10.1016/j.jbankfin.2021.106045

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