Short Sales and Trade Classification Algorithms
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.
|Date of creation:||Jul 2008|
|Date of revision:|
|Publication status:||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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University of St. Gallen Department of Economics working paper series 2003
2003-01, Department of Economics, University of St. Gallen.
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