Inferring Trade Direction from Intraday Data




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    • Charles M. C. Lee is an assistant professor of accounting at the University of Michigan, Ann Arbor. Mark J. Ready is an assistant professor of finance at the University of Wisconsin, Madison. We wish to thank the participants in the New York Stock Exchange Visitor's Center Program, especially specialists Joseph Mahoney of AC Partners and William E. Boye, Jr. of Webco Securities Inc., for their cooperation and tutelage. Helpful comments and suggestions were also received from Joel Hasbrouck, Maureen O'Hara, Seymour Smidt, participants of the Finance Workshop at Cornell University, and an anonymous referee. The financial support from the Social Sciences and Humanities Research Council of Canada and the Deloittes, Haskins and Sells Foundation is gratefully acknowledged. This research is conducted using the Cornell National Supercomputer Facility, a resource of the Cornell Theory Center, which receives major funding from the National Science Foundation and IBM Corporation.


This paper evaluates alternative methods for classifying individual trades as market buy or market sell orders using intraday trade and quote data. We document two potential problems with quote-based methods of trade classification: quotes may be recorded ahead of trades that triggered them, and trades inside the spread are not readily classifiable. These problems are analyzed in the context of the interaction between exchange floor agents. We then propose and test relatively simple procedures for improving trade classifications.