Short Sales, Long Sales, and the Lee-Ready Trade Classification Algorithm Revisited

42 Pages Posted: 7 Feb 2011 Last revised: 12 Jan 2012

See all articles by Bidisha Chakrabarty

Bidisha Chakrabarty

Saint Louis University - Richard A. Chaifetz School of Business

Pamela C. Moulton

Cornell University - SC Johnson College of Business

Andriy Shkilko

Wilfrid Laurier University - Lazaridis School of Business and Economics

Multiple version iconThere are 2 versions of this paper

Date Written: January 12, 2012

Abstract

Asquith, Oman, and Safaya (2010) conclude that short sales are often misclassified by the Lee-Ready algorithm. The algorithm identifies most short sales as buyer-initiated, whereas the authors posit that short sales should be overwhelmingly seller-initiated. Using order data to identify true trade initiator, we document that short sales are, in fact, predominantly buyer-initiated and that the Lee-Ready algorithm correctly classifies most of them. Misclassification rates for short and long sales are near zero at the daily level. At the trade level, misclassification rates are 31% using contemporaneous quotes and trades and decline to 21% when quotes are lagged one second.

Keywords: Trade Classification, Short Sales, Lee-Ready, Trade Initiation

JEL Classification: G10, G18

Suggested Citation

Chakrabarty, Bidisha and Moulton, Pamela C. and Shkilko, Andriy, Short Sales, Long Sales, and the Lee-Ready Trade Classification Algorithm Revisited (January 12, 2012). Available at SSRN: https://ssrn.com/abstract=1755025 or http://dx.doi.org/10.2139/ssrn.1755025

Bidisha Chakrabarty

Saint Louis University - Richard A. Chaifetz School of Business ( email )

3674 Lindell Blvd
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United States
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3149771479 (Fax)

HOME PAGE: http://business.slu.edu/departments/finance/faculty-staff/bidisha-chakrabarty

Pamela C. Moulton (Contact Author)

Cornell University - SC Johnson College of Business ( email )

Ithaca, NY 14853
United States

Andriy Shkilko

Wilfrid Laurier University - Lazaridis School of Business and Economics ( email )

LH 4050
75 University Ave. W.
Waterloo, Ontario N2L3C5
Canada
519.884.0710 ext. 2462 (Phone)
519.884.0201 (Fax)

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