Discerning Information from Trade Data

56 Pages Posted: 23 Jan 2012 Last revised: 16 May 2016

See all articles by David Easley

David Easley

Cornell University - Department of Economics; Cornell University - Department of Information Science

Marcos Lopez de Prado

Cornell University - Operations Research & Industrial Engineering; AQR Capital Management, LLC

Maureen O'Hara

Cornell University - Samuel Curtis Johnson Graduate School of Management

Date Written: March 1, 2015

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 in which tick rules or bulk volume classification will predominate.

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

JEL Classification: C02, D52, D53, G14

Suggested Citation

Easley, David and López de Prado, Marcos and O'Hara, Maureen, Discerning Information from Trade Data (March 1, 2015). Journal of Financial Economics, 120(2), pp. 269-286. May 2016; Johnson School Research Paper Series No. 8-2012. Available at SSRN: https://ssrn.com/abstract=1989555 or http://dx.doi.org/10.2139/ssrn.1989555

David Easley (Contact Author)

Cornell University - Department of Economics ( email )

414 Uris Hall
Ithaca, NY 14853-7601
United States
607-255-6283 (Phone)
607-255-2818 (Fax)

Cornell University - Department of Information Science ( email )

402 Bill & Melinda Gates Hall
Ithaca, NY 14853
United States

Marcos López de Prado

Cornell University - Operations Research & Industrial Engineering ( email )

237 Rhodes Hall
Ithaca, NY 14853
United States

HOME PAGE: http://www.orie.cornell.edu

AQR Capital Management, LLC

One Greenwich Plaza
Greenwich, CT 06830
United States

HOME PAGE: http://www.aqr.com

Maureen O'Hara

Cornell University - Samuel Curtis Johnson Graduate School of Management ( email )

Ithaca, NY 14853
United States
607-255-3645 (Phone)
607-255-5993 (Fax)

Register to save articles to
your library

Register

Paper statistics

Downloads
5,505
rank
1,229
Abstract Views
18,632
PlumX Metrics
!

Under construction: SSRN citations will be offline until July when we will launch a brand new and improved citations service, check here for more details.

For more information