Griffin, J;
Oberoi, J;
Oduro, S;
(2021)
Estimating the probability of informed trading: a Bayesian approach.
Journal of Banking and Finance
, 125
, Article 106045. 10.1016/j.jbankfin.2021.106045.
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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.
| Type: | Article |
|---|---|
| Title: | Estimating the probability of informed trading: a Bayesian approach |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.jbankfin.2021.106045 |
| Publisher version: | https://doi.org/10.1016/j.jbankfin.2021.106045 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | PIN, software, Bayesian estimation, information asymmetry risk, robust estimation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10118386 |
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