Discerning information from trade data

David Easley, Marcos Lopez de Prado and Maureen O'Hara

Journal of Financial Economics, 2016, vol. 120, issue 2, 269-285

Abstract: How best to discern trading intentions from market data? We examine the accuracy of three methods for classifying trade data: bulk volume classification (BVC), tick rule and aggregated tick rule. We develop a Bayesian model of inferring information from trade executions and show the conditions under which tick rules or bulk volume classification predominates. Empirically, we find that tick rule approaches and BVC are relatively good classifiers of the aggressor side of trading, but bulk volume classifications are better linked to proxies of information-based trading. Thus, BVC would appear to be a useful tool for discerning trading intentions from market data.

Keywords: Trade classification; Bulk volume classification; Flow toxicity; Volume imbalance; Market microstructure (search for similar items in EconPapers)
JEL-codes: C02 D52 D53 G14 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (36)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jfinec:v:120:y:2016:i:2:p:269-285

DOI: 10.1016/j.jfineco.2016.01.018

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