Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/22858
Authors: 
Grammig, Joachim G.
Theissen, Erik
Year of Publication: 
2002
Series/Report no.: 
Bonn econ discussion papers 2002,37
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.
Subjects: 
Informed trading
market microstructure
trade classification
JEL: 
C52
G10
G14
Document Type: 
Working Paper

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