Modeling Trade Direction

25 Pages Posted: 27 Nov 2007 Last revised: 18 Oct 2011

Dale W. R. Rosenthal

University of Illinois at Chicago - Department of Finance

Multiple version iconThere are 2 versions of this paper

Date Written: August 6, 2008

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 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

Rosenthal, Dale W. R., Modeling Trade Direction (August 6, 2008). Available at SSRN: https://ssrn.com/abstract=1032701 or http://dx.doi.org/10.2139/ssrn.1032701

Dale W. R. Rosenthal (Contact Author)

University of Illinois at Chicago - Department of Finance ( email )

2431 University Hall (UH)
601 S. Morgan Street
Chicago, IL 60607-7124
United States

HOME PAGE: http://tigger.uic.edu/~daler

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