Testing the Bulk Volume Classification Algorithm

54 Pages Posted: 20 Feb 2021

See all articles by Allen Carrion

Allen Carrion

University of Memphis - Fogelman College of Business and Economics

Madhuparna Kolay

University of Portland - Dr. Robert B. Pamplin, Jr. School of Business Administration

Date Written: December 2020

Abstract

We document that the existing evidence that bulk volume trade classification (BVC) measures informed trading arises largely due to mis-specified tests. Simulations show that these tests detect spurious relationships in data containing only uninformed liquidity trades. We also assess the performance of BVC order imbalances in the NASDAQ HFT dataset, showing that BVC order imbalances underperform conventional order imbalance measures in detecting informed trading. The component of order flow designated by BVC as passive informed trading fails to predict returns with the correct sign. On balance, our evidence supports the use of conventional order imbalance measures to identify informed trading.

Keywords: Market Microstructure, Informed Trading, High-frequency Trading, Bulk Volume Classification, Trade classification, Order Imbalances, Simulation, Estimator Properties

JEL Classification: C18, G10, G14

Suggested Citation

Carrion, Allen and Kolay, Madhuparna, Testing the Bulk Volume Classification Algorithm (December 2020). Available at SSRN: https://ssrn.com/abstract=3746731 or http://dx.doi.org/10.2139/ssrn.3746731

Allen Carrion (Contact Author)

University of Memphis - Fogelman College of Business and Economics ( email )

Memphis, TN 38152
United States

Madhuparna Kolay

University of Portland - Dr. Robert B. Pamplin, Jr. School of Business Administration ( email )

Portland, OR 97203
United States

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