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Estimating the Probability of Informed Trading: A Bayesian approach

Griffin, Jim E., Oberoi, Jaideep S, Oduro, Samuel Dua (2021) Estimating the Probability of Informed Trading: A Bayesian approach. Journal of Banking & Finance, 125 . Article Number 106045. ISSN 0378-4266. (doi:10.1016/j.jbankfin.2021.106045) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:85796)

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Language: English

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https://doi.org/10.1016/j.jbankfin.2021.106045

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.

Item Type: Article
DOI/Identification number: 10.1016/j.jbankfin.2021.106045
Uncontrolled keywords: software, PIN, Bayesian estimation, information asymmetry risk
Divisions: Divisions > Kent Business School - Division > Department of Accounting and Finance
Depositing User: Jaideep Oberoi
Date Deposited: 02 Feb 2021 16:42 UTC
Last Modified: 07 Oct 2021 13:30 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/85796 (The current URI for this page, for reference purposes)
Griffin, Jim E.: https://orcid.org/0000-0002-4828-7368
Oberoi, Jaideep S: https://orcid.org/0000-0002-1101-7612
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