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.
Acknowledgements: We would like to thank Thomas Covert, Amy Edwards, SP Kothari, Ryan LaFond, Parag Pathak, Mark Ready, Jeri Seidman, Avanidhar Subrahmanyam, Erik Theissen, and Jiang Wang for helpful discussions and comments. We would also like to thank Ted Keith for research assistance. The views expressed herein are those of the author(s) and do not necessarily reflect the views of the National Bureau of Economic Research.
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.