Estimating the probability of informed trading: A Bayesian approach

被引：3

作者：

Griffin, Jim ^{[1
]}

Oberoi, Jaideep ^{[2
]}

Oduro, Samuel D. ^{[3
]}

机构：

[1] UCL, Dept Stat Sci, Gower St, London WC1E 6BT, England

[2] Univ Kent, Kent Business Sch, Parkwood Rd, Canterbury CT2 7FS, Kent, England

[3] easyJet Airline Co, Data Sci & Analyt, Hangar 89, Luton LU2 9PF, Beds, England

来源：

JOURNAL OF BANKING & FINANCE | 2021年 / 125卷

关键词：

PIN; software; Bayesian estimation; information asymmetry risk; robust estimation;

D O I：

10.1016/j.jbankfin.2021.106045

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

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.

引用

页数：22

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