A New Approach for Detecting High-Frequency Trading from Order and Trade Data

16 Pages Posted: 11 Jul 2017

See all articles by Cumhur Ekinci

Cumhur Ekinci

Istanbul Technical University

Oguz Ersan

Kadir Has University, Accounting and Financial Management Department, Faculty of Management

Date Written: July 5, 2017

Abstract

We suggest a two-step approach in detecting HFT activity from order and trade data. While the first step focuses on multiple actions of an order submitter in low latency, the second searches for the surroundings of these orders to link related orders. On a sample of 2015 data from Borsa Istanbul, we estimate that average HFT involvement is 1.23%. HFT activity is generally higher in large cap stocks (2.88%). Most HFT orders are in the form of very rapidly canceled order submissions. A robustness check reveals a mean accuracy rate of 97% in the linkage of orders.

Keywords: High-frequency trading (HFT), HFT detection, Low latency trading, Borsa Istanbul

JEL Classification: G10, G12, G15, G23

Suggested Citation

Ekinci, Cumhur and Ersan, Oguz, A New Approach for Detecting High-Frequency Trading from Order and Trade Data (July 5, 2017). Available at SSRN: https://ssrn.com/abstract=2997509 or http://dx.doi.org/10.2139/ssrn.2997509

Cumhur Ekinci (Contact Author)

Istanbul Technical University ( email )

ITU Isletme Fakultesi - Macka
Istanbul, 34367
Turkey

HOME PAGE: http://akademi.itu.edu.tr/ekincicu/

Oguz Ersan

Kadir Has University, Accounting and Financial Management Department, Faculty of Management ( email )

Cibali Mah., Fatih
Istanbul, 34083
Turkey

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