NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH

Short Sales and Trade Classification Algorithms

Paul Asquith, Rebecca Oman, Christopher Safaya

NBER Working Paper No. 14158
Issued in July 2008
NBER Program(s):   AP

This paper demonstrates that short sales are often misclassified as buyer-initiated by the Lee-Ready and other commonly used trade classification algorithms. This result is due in part to regulations which require short sales be executed on an uptick or zero-uptick. In addition, while the literature considers "immediacy premiums" in determining trade direction, it ignores the often larger borrowing premiums which short sellers must pay. Since short sales constitute approximately 30% of all trade volume on U.S. exchanges, these results are important to the empirical market microstructure literature as well as to measures that rely upon trade classification, such as the probability of informed trading (PIN) metric.

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Published: Asquith, Paul & Oman, Rebecca & Safaya, Christopher, 2010. "Short sales and trade classification algorithms," Journal of Financial Markets, Elsevier, vol. 13(1), pages 157-173, February.

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