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) (KAR id:85796)
PDF
Author's Accepted Manuscript
Language: English
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
|
|
Download this file (PDF/4MB) |
Preview |
Request a format suitable for use with assistive technology e.g. a screenreader | |
Official URL: 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: | 05 Nov 2024 12:51 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/85796 (The current URI for this page, for reference purposes) |
- Link to SensusAccess
- Export to:
- RefWorks
- EPrints3 XML
- BibTeX
- CSV
- Depositors only (login required):