Short Sales and Trade Classification Algorithms

Paul Asquith, Rebecca Oman and Christopher Safaya

No 14158, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: 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.

JEL-codes: G10 G12 G18 (search for similar items in EconPapers)
Date: 2008-07
New Economics Papers: this item is included in nep-mst
Note: AP
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Citations: View citations in EconPapers (4)

Published as 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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