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Short Sales and Trade Classification AlgorithmsPaul AsquithMassachusetts Institute of Technology (MIT) - Economics, Finance, Accounting (EFA); National Bureau of Economic Research (NBER) Rebecca OmanMassachusetts Institute of Technology (MIT) Christopher SafayaMassachusetts 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 working papers seriesDate posted: July 16, 2008Suggested CitationContact Information
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