Short sales and trade classification algorithms
By: Paul Asquith, Rebecca Oman, Christopher Safaya.
Contributors: Oman, Rebecca.; Safaya, Christopher.; National Bureau of Economic Research.
Series: NBER working paper series -- working paper 14158; Working paper series (National Bureau of Economic Research : Online) -- working paper no. 14158.
Publisher: National Bureau of Economic Research
Published: 2008
Place of publication: Cambridge, MA
Language: eng
Format: Electronic resource
Description: "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"--National Bureau of Economic Research web site.
Notes: Title from PDF file as viewed on 7/23/2008.

Includes bibliographical references.

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