25 Pages Posted: 27 Nov 2007 Last revised: 18 Oct 2011
Date Written: August 6, 2008
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 2,800 US stocks show modeled classifications are 1-2% more accurate than current methods across dates, sectors, and the spread. For NASDAQ and NYSE 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.
Keywords: trade classification, delay models, trade publishing delays, prevailing quotes, trade direction, flash crash detection
JEL Classification: C53, D82, G14
Suggested Citation: Suggested Citation