Response and Liquidity Risk Modeling of High-Frequency Trading Strategies under Extreme Market Events

DOI

10.2991/978-94-6463-748-9_114How to use a DOI?

Keywords

High-Frequency Trading (HFT); Market Liquidity; Extreme Market Events

Abstract

This study explores the response characteristics of high-frequency trading strategies under extreme market events and their impact on market liquidity. Based on the high-frequency trading data of the Industrial and Commercial Bank of China (601398) during the A-share market volatility in March 2022, this paper analyzes the relationship between ghost liquidity indicators (withdrawal rate and ghost order ratio) and market liquidity, constructs a multiple linear regression model, and studies the influence mechanism of high-frequency trading behavior on market liquidity. The results show that the increase of ghost order ratio leads to the increase of bid-ask spread significantly, while the effect of withdrawal rate on bid-ask spread is relatively weak. During extreme market events, HFT exhibited a clear liquidity withdrawal characteristic, with the withdrawal rate exceeding 50% and bid-ask spreads widening significantly when market volatility increased in mid-March. Through the hysteresis effect analysis, it is found that there is a significant time dependence between ghost liquidity and market trading indicators. The study suggests to strengthen the supervision of ghost liquidity behavior and restrict the pending order behavior that does not have the actual trading intention. In the future, the research can be expanded to different markets and asset classes, introducing more macroeconomic variables, and using nonlinear models to improve forecasting power. This study provides a new empirical basis for understanding the behavior characteristics of high-frequency trading under extreme market conditions.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Zhanpeng Jin
PY  - 2025
DA  - 2025/07/03
TI  - Response and Liquidity Risk Modeling of High-Frequency Trading Strategies under Extreme Market Events
BT  - Proceedings of the 2025 International Conference on Financial Risk and Investment Management (ICFRIM 2025)
PB  - Atlantis Press
SP  - 1056
EP  - 1065
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-748-9_114
DO  - 10.2991/978-94-6463-748-9_114
ID  - Jin2025
ER  -