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The Accuracy of Trade Classification Rules:Evidence from Nasdaq

Published online by Cambridge University Press:  06 April 2009

Katrina Ellis ,
Roni Michaely  and
Maureen O'Hara
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Abstract

Researchers are increasingly using data from the Nasdaqmarket to examine pricing behavior, market design,and other microstructure phenomena. The validity ofany study that classifies trades as buys or sellsdepends on the accuracy of the classificationmethod. Using a Nasdaq proprietary data set thatidentifies trade direction, we examine the validityof several trade classification algorithms. We findthat the quote rule, the tick rule, and the Lee andReady (1991) rule correctly classify 76.4%, 77.66%,and 81.05% of the trades, respectively. However, allclassification rules have only a very limitedsuccess in classifying trades executed inside thequotes, introducing a bias in the accuracy ofclassifying large trades, trades during high volumeperiods, and ECN trades. We also find that extantalgorithms do a mediocre job when used forcalculating effective spreads. For Nasdaq trades, wepropose a new and simple classification algorithmthat improves over extant algorithms.

Information

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 35 , Issue 4 , December 2000 , pp. 529 - 551
Copyright
Copyright © School of Business Administration, University of Washington 2000

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Footnotes

*

Ellis, Australian Graduate School of Management;Michaely, Cornell University and Tel-AviaUniversity; O'Hara, Cornell University. Theauthors thank Dean Furbush, Tim McCormick, andJennifer Drake of the NASD Economic ResearchDepartment for extensive help in providing thedata setused in this paper. We thank the editor(Paul Malatesta), Jeffrey Harris, SoerenHvidkjaer, Tim McCormick, and Paul Schultz foruseful comments. We are particularly grateful toHank Bessembinder (associate editor and referee)for helpful suggestions. Please addresscorrespondence to Roni Michaely (rm34@cornell.edu) or Maureen O'Hara(mo19@cornell.edu) atthe Johnson Graduate School of Management, CornellUniversity, Ithaca, NY 14853.

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