Does the Probability of Informed Trading Model Fit Empirical Data?

43 Pages Posted: 24 Oct 2014 Last revised: 7 Aug 2015

See all articles by Quan Gan

Quan Gan

The University of Sydney - Discipline of Finance; Financial Research Network (FIRN)

Wang Chun Wei

University of Queensland - Faculty of Business, Economics and Law; University of Queensland - Finance

David Johnstone

University of Sydney Business School; Financial Research Network (FIRN)

Date Written: August 3, 2015

Abstract

The probability of informed trading (PIN) is used widely as a measure of information asymmetry. Relatively little work has appeared on how well PIN models fit empirical trade data. We reveal structural limitations in PIN models by examining their marginal distributions and dependence structures represented by copulas. We develop a distribution-free test of the goodness-of-fit of PIN models. Our results indicate that estimated PIN models have generally poor fit to actual trade data. These results suggest that researchers should be cautious when PIN estimates are plugged into empirical models as explanatory variables.

Keywords: PIN, dependence structure, copula, mixture model, Rosenblatt's transformation, goodness-of-fit test

JEL Classification: C52, G14

Suggested Citation

Gan, Quan and Wei, Wang Chun and Johnstone, David, Does the Probability of Informed Trading Model Fit Empirical Data? (August 3, 2015). Available at SSRN: https://ssrn.com/abstract=2514119 or http://dx.doi.org/10.2139/ssrn.2514119

Quan Gan (Contact Author)

The University of Sydney - Discipline of Finance ( email )

Discipline of Finance
University of Sydney
Sydney, NSW 2006
Australia

HOME PAGE: http://sydney.edu.au/business/staff/quang

Financial Research Network (FIRN) ( email )

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

HOME PAGE: http://www.firn.org.au

Wang Chun Wei

University of Queensland - Faculty of Business, Economics and Law ( email )

4072 Brisbane, Queensland
Australia

University of Queensland - Finance ( email )

Australia

David Johnstone

University of Sydney Business School ( email )

Instute of Transport and Logistics Studies (C37)
The University of Sydney
Sydney, NSW 2133
Australia

Financial Research Network (FIRN)

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

HOME PAGE: http://www.firn.org.au

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