A new approach for detecting high-frequency trading from order and trade data


Ekinci C. E. , Ersan O.

Finance Research Letters, vol.24, pp.199-220, 2018 (Journal Indexed in SCI Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 24
  • Publication Date: 2018
  • Doi Number: 10.1016/j.frl.2017.09.020
  • Title of Journal : Finance Research Letters
  • Page Numbers: pp.199-220

Abstract

© 2017 Elsevier Inc.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.