Template-Type: ReDIF-Paper 1.0
Title: Estimating the Probability of Informed Trading - Does Trade Misclassification Matter?
Author-Name: Joachim Grammig
Author-Name: Erik Theissen
Author-Email: 
Classification-JEL: C52, G10, G14
Keywords: Informed trading, market microstructure, trade classification
Abstract: Easley / Kiefer / O'Hara / Paperman (1996) (EKOP) have proposed an empirical methodology that allows to estimate the probability of informed trading 
	and that has subsequently been used to address a wide range of issues in market microstructure. The data needed for estimation is the number of buyer- and 
	seller-initiated trades. This information often has to be inferred by applying trade classification algorithms like the one proposed by Lee / Ready (1991). These 
	algorithms are known to be inaccurate. In this paper we perform extensive simulations to show that inaccurate trade classification leads to biased estimation of 
	the probability of informed trading when applying the EKOP methodology. The estimate is biased downward and the magnitude of the bias is related to the 
	trading intensity of the stock in question. Scrutinizing prior empirical studies using the EKOP methodology, we conclude that the bias may severely affect the 
	results of empirical microstructure studies. 
Note: 
Length: 24
Creation-Date: 2002-12	
Revision-Date: 
File-URL: http://www.wiwi.uni-bonn.de/bgsepapers/bonedp/bgse37_2002.pdf
File-Format: application/pdf
Handle: RePEc:bon:bonedp:bgse37_2002