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Short Sales and Trade Classification Algorithms


Paul Asquith


Massachusetts Institute of Technology (MIT) - Economics, Finance, Accounting (EFA); National Bureau of Economic Research (NBER)

Rebecca Oman


Massachusetts Institute of Technology (MIT)

Christopher Safaya


Massachusetts Institute of Technology (MIT)

July 2008

NBER Working Paper No. w14158

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.

Number of Pages in PDF File: 32

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Date posted: July 16, 2008  

Suggested Citation

Asquith, Paul, Oman, Rebecca and Safaya, Christopher, Short Sales and Trade Classification Algorithms (July 2008). NBER Working Paper No. w14158. Available at SSRN: http://ssrn.com/abstract=1161041

Contact Information

Paul Asquith (Contact Author)
Massachusetts Institute of Technology (MIT) - Economics, Finance, Accounting (EFA) ( email )
77 Massachusetts Avenue
Cambridge, MA 02139-4307
United States
National Bureau of Economic Research (NBER)
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
Rebecca Oman
Massachusetts Institute of Technology (MIT) ( email )
77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States
Christopher Safaya
Massachusetts Institute of Technology (MIT) ( email )
77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States
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