Short sales and trade classification algorithms
Name
Asquith_Short sales.pdf
Size
214.85 KB
Format
Adobe PDF
Checksum (MD5)
78b6c9e67d4335c097a7df5e3807048b
Author(s)
Asquith, Paul
Oman, Rebecca
Safaya, Christopher
Date Issued
September 2009
Journal
Journal of Financial Markets
Publisher
Elsevier
Citation
Asquith, Paul, Rebecca Oman, and Christopher Safaya. “Short Sales and Trade Classification Algorithms.” Journal of Financial Markets 13, no. 1 (February 2010): 157–173.
Version
Author's final manuscript
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 that 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 that 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.
MIT Department
Sloan School of Management
Terms of Use
Creative Commons Attribution-Noncommercial-NoDerivatives
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/j.finmar.2009.09.005
