Modeling Trade Direction
The Journal of Financial Econometrics, 2012, vol. 10, issue 2, 390-415
I propose a modeling approach to classifying trades as buys or sells. Modeled classifications consider information strengths, microstructure effects, and classification correlations. I also propose estimators for quotes prevailing at trade time. Comparisons using 2800 U.S. stocks show modeled classifications are 1%--2% more accurate than current methods across dates, sectors, and the spread. For Nasdaq and New York Stock Exchange stocks, 1% and 1.3% of improvement comes from using information strengths; 0.9% and 0.7% of improvement comes from estimating quotes. I find evidence past studies used unclean data and indications of short-term price predictability. The method may help detect destabilizing order flow. Copyright The Author 2012. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: email@example.com., Oxford University Press.
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Working Paper: Modeling Trade Direction (2008)
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