Modeling Trade Direction

Journal of Financial Econometrics, Vol. 10, No. 2, pp. 390-415, 2012

Posted: 8 Oct 2012

Multiple version iconThere are 2 versions of this paper

Date Written: 2012

Abstract

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.

Keywords: delay models, flash crash detection, prevailing quotes, trade classification, trade direction, trade publishing delays

JEL Classification: C53, D82, G14

Suggested Citation

Rosenthal, Dale W. R., Modeling Trade Direction (2012). Journal of Financial Econometrics, Vol. 10, No. 2, pp. 390-415, 2012, Available at SSRN: https://ssrn.com/abstract=2158424

Dale W. R. Rosenthal (Contact Author)

Department of Finance ( email )

Notre Dame, IN
United States

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