Short sales and trade classification algorithms
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.
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References listed on IDEAS
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- Odders-White, Elizabeth R., 2000. "On the occurrence and consequences of inaccurate trade classification," Journal of Financial Markets, Elsevier, vol. 3(3), pages 259-286, August.
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University of St. Gallen Department of Economics working paper series 2003
2003-01, Department of Economics, University of St. Gallen.
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- Theissen, Erik, 2001. "A test of the accuracy of the Lee/Ready trade classification algorithm," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 11(2), pages 147-165, June.
- Alexander, Gordon J. & Peterson, Mark A., 2008. "The effect of price tests on trader behavior and market quality: An analysis of Reg SHO," Journal of Financial Markets, Elsevier, vol. 11(1), pages 84-111, February.
- Ellis, Katrina & Michaely, Roni & O'Hara, Maureen, 2000. "The Accuracy of Trade Classification Rules: Evidence from Nasdaq," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(04), pages 529-551, December.
- Bessembinder, Hendrik, 2003. "Trade Execution Costs and Market Quality after Decimalization," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 38(04), pages 747-777, December.
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