High-frequency trading, stock volatility, and intraday crashes

被引：6

作者：

Ben Ammar, Imen ^{[1
]}

Hellara, Slaheddine ^{[1
]}

机构：

[1] Univ Tunis, Dept Finance & Accounting, ISGT, LR99ES04 BESTMOD, Tunis 2000, Tunisia

来源：

QUARTERLY REVIEW OF ECONOMICS AND FINANCE | 2022年 / 84卷

关键词：

Algorithmic trading; High-frequency trading; Market microstructure; Stock volatility; Intraday crashes; RANGE-BASED ESTIMATION; PANEL-DATA; REALIZED VARIANCE; MARKET; LIQUIDITY;

D O I：

10.1016/j.qref.2022.03.004

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

We examine the effect of high-frequency trading (HFT) on the price volatility of Euronext-listed stocks. Under stable market conditions, greater HFT intensity is associated with decreased stock price volatility. However, during periods of intraday crashes, rapid interactions between HFT algorithms lead to high rates of order cancellations and simultaneous withdrawals of high-frequency traders from the limit order book. High-frequency traders submit aggressive orders during these periods and consume more liquidity than they provide, resulting in increased stock price volatility.(c) 2022 Board of Trustees of the University of Illinois. Published by Elsevier Inc. All rights reserved.

引用

页码：337 / 344

页数：8

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