Download this Paper Open PDF in Browser

Estimating the Probability of Informed Trading - Does Trade Misclassification Matter?

39 Pages Posted: 3 Mar 2006  

Ekkehart Boehmer

Singapore Management University - Lee Kong Chian School of Business

Joachim Grammig

Eberhard Karls Universitaet Tübingen; Centre for Financial Research (CfR); Center for Financial Studies (CfS)

Erik Theissen

University of Mannheim - Finance Area

Multiple version iconThere are 2 versions of this paper

Date Written: February 25, 2006

Abstract

Easley et al. (1996) have proposed an empirical methodology to estimate the probability of informed trading (PIN). This approach has been employed in a wide range of applications in market microstructure, corporate finance, and asset pricing. To estimate the model, a researcher only needs the number of buyer- and seller-initiated trades. This information, however, is generally unobservable and has to be inferred from trade-classification algorithms, which are known to be inaccurate. In this paper, we show analytically that inaccurate trade classification leads to downward biased PIN estimates and that the magnitude of the bias is related to a security's trading intensity. Simulation results and empirical evidence based on order and transaction data from the New York Stock Exchange are consistent with this argument. We propose a data-based adjustment procedure that substantially reduces the misclassification bias.

Notes: A previous version of this paper can be found at: http://ssrn.com/abstract=367041.

Keywords: Informed trading, market microstructure, trade classification

JEL Classification: G12, G14, C52

Suggested Citation

Boehmer, Ekkehart and Grammig, Joachim and Theissen, Erik, Estimating the Probability of Informed Trading - Does Trade Misclassification Matter? (February 25, 2006). Available at SSRN: https://ssrn.com/abstract=887221 or http://dx.doi.org/10.2139/ssrn.887221

Ekkehart Boehmer (Contact Author)

Singapore Management University - Lee Kong Chian School of Business ( email )

Singapore

Joachim Grammig

Eberhard Karls Universitaet Tübingen ( email )

Mohlstrasse 36
D-72074 Tuebingen, 72074
Germany

HOME PAGE: http://www.uni-tuebingen.de/uni/wwo/Grammig/grammigeng.html

Centre for Financial Research (CfR) ( email )

Albertus-Magnus Platz
Cologne, 50923
Germany

Center for Financial Studies (CfS) ( email )

Taunusanlage 6
Frankfurt/Germany, D-60329
Germany

Erik Theissen

University of Mannheim - Finance Area ( email )

Mannheim, 68131
Germany

Paper statistics

Downloads
766
Rank
25,754
Abstract Views
4,625