Short Sales and Trade Classification Algorithms / Paul Asquith, Rebecca Oman, Christopher Safaya.

Format:

Book

Author/Creator:

Asquith, Paul.

Contributor:

National Bureau of Economic Research.

Oman, Rebecca.

Safaya, Christopher.

Series:

Working Paper Series (National Bureau of Economic Research) no. w14158.

NBER working paper series no. w14158

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2008.

Summary:

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.

Notes:

Print version record

July 2008.