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

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

File(s)
Moulton2_Short_sales_long_sales.pdf (545.71 KB)
Permanent Link(s)
https://hdl.handle.net/1813/72030
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SHA Articles and Chapters
Author
Chakrabarty, Bidisha
Moulton, Pamela
Shkilko, Andriy
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.

Date Issued
2012-01-12
Keywords
Lee-Ready algorithm
•
short sales
•
classification
Related DOI
https://doi.org/10.1016/j.finmar.2012.01.001
Rights
Required Publisher Statement: © Elsevier. Final version published as: Chakrabarty, B., Moulton, P. C, & Shkilko, A. (2012). Short sales, long sales, and the Lee-Ready trade classification algorithm revisited. Journal of Financial Markets, 15(4), 467-491. Reprinted with permission. All rights reserved.
Type
article

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