Bulk Volume Classification and Information Detection

40 Pages Posted: 11 Oct 2014 Last revised: 15 Apr 2019

See all articles by Marios A. Panayides

Marios A. Panayides

University of Cyprus - Department of Accounting and Finance; University of Pittsburgh - Katz Graduate School of Business

Thomas Shohfi

Rensselaer Polytechnic Institute (RPI) - Department of Finance and Accounting

Jared D. Smith

North Carolina State University - Poole College of Management

Date Written: April 14, 2019

Abstract

Using European stock data from two different venues and time periods for which we can identify each trade’s aggressor, we test the performance of the bulk volume classification (Easley et al. (2016); BVC) algorithm. BVC is data efficient, but may identify trade aggressors less accurately than “bulk” versions of traditional trade-level algorithms. BVC-estimated trade flow is the only algorithm related to proxies of informed trading, however. This is because traditional algorithms are designed to find individual trade aggressors, but we find that trade aggressor no longer captures information. Finally, we find that after calibrating BVC to trading characteristics in out-of-sample data, it is better able to detect information and to identify trade aggressors. In the new era of fast trading, sophisticated investors, and smart order execution, BVC appears to be the most versatile algorithm.

Keywords: Classification algorithms; bulk volume; informed trading strategies

JEL Classification: G11, G12, G14, G18

Suggested Citation

Panayides, Marios A. and Shohfi, Thomas and Smith, Jared D., Bulk Volume Classification and Information Detection (April 14, 2019). Journal of Banking and Finance, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2503628 or http://dx.doi.org/10.2139/ssrn.2503628

Marios A. Panayides

University of Cyprus - Department of Accounting and Finance ( email )

University of Cyprus
P.O. Box 20537
Nicosia, CY-1678
Cyprus

University of Pittsburgh - Katz Graduate School of Business ( email )

372 Mervis Hall
Pittsburgh, PA 15260
United States

Thomas Shohfi (Contact Author)

Rensselaer Polytechnic Institute (RPI) - Department of Finance and Accounting ( email )

Pittsburgh Building
110 8th street
Troy, NY 12180
United States

HOME PAGE: http://shohfi.com/

Jared D. Smith

North Carolina State University - Poole College of Management ( email )

Nelson Hall
Raleigh, NC 27695-8614
United States

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