Logo
Munich Personal RePEc Archive

Modeling Trade Direction

Rosenthal, Dale W.R. (2008): Modeling Trade Direction. Forthcoming in: Journal of Financial Econometrics

Warning
There is a more recent version of this item available.
[thumbnail of MPRA_paper_36784.pdf]
Preview
PDF
MPRA_paper_36784.pdf

Download (3MB) | Preview

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.

Available Versions of this Item

Atom RSS 1.0 RSS 2.0

Contact us: mpra@ub.uni-muenchen.de

This repository has been built using EPrints software.

MPRA is a RePEc service hosted by Logo of the University Library LMU Munich.