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Modeling Trade Direction

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Title: Modeling Trade Direction
Author(s): Rosenthal, Dale W. R.
Subject(s): trade classification delay models trade publishing delays prevailing quotes trade direction flash crash detection
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. (JEL: C53, D82, G14)
Issue Date: 2008-08
Publisher: Oxford University Press
Citation Info: Rosenthal, D. W. R. (2012). "Modeling Trade Direction." Journal of Financial Econometrics 10(2): 390-415. DOI: 10.1093/jjfinec/nbr014
Type: Article
Description: This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Journal of Financial Econometrics following peer review. The definitive publisher-authenticated version Rosenthal, D. W. R. (2012). "Modeling Trade Direction." Journal of Financial Econometrics 10(2): 390-415. DOI: 10.1093/jjfinec/nbr014 is available online at: oxfordjournals.org
URI: http://hdl.handle.net/10027/10479
ISSN: 1479-8409
Sponsor: National Science Foundation under grants DMS 06-04758 and SES 06-31605
Date Available in INDIGO: 2013-11-12
 

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