Impact of Pinging in Financial Markets: An Agent Based Study

Sriram Bharadwaj Rangarajan, Carmine Ventre

2025

Abstract

Institutional traders in the financial markets rely on hidden trading venues to execute significantly large trades with lower execution costs and reduced information leakage. One such trading venue, known as dark pool, offers institutional traders better execution costs through hidden order books and delayed trade reporting. Despite their advantages, dark pools are susceptible to market manipulation practices such as ’pinging’. Due to low transparency in dark pools, the incentives of pinging agents and their impact on market participants has not been studied in detail. In this paper, we present an agent-based model of the financial markets to study market impact of trading strategies and the dynamics of pinging in dark pools. We identify the scenarios and market conditions under which pinging is a profitable manipulation strategy and compute its impact on execution costs of informed institutional trading agents. Further, we consider agent incentives and use empirical game theory to compute the equilibrium state of the market and quantify the additional costs imposed by pinging agents on informed traders. This study aims to bridge the existing research gap by providing a framework for analyzing market manipulation in dark pools and is a foundational step towards designing safer dark pools.

Paper Citation

in Harvard Style

Rangarajan S. and Ventre C. (2025). Impact of Pinging in Financial Markets: An Agent Based Study. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 172-183. DOI: 10.5220/0013312900003890

in Bibtex Style

@conference{icaart25,
author={Sriram Rangarajan and Carmine Ventre},
title={Impact of Pinging in Financial Markets: An Agent Based Study},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2025},
pages={172-183},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013312900003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Impact of Pinging in Financial Markets: An Agent Based Study
SN - 978-989-758-737-5
AU - Rangarajan S.
AU - Ventre C.
PY - 2025
SP - 172
EP - 183
DO - 10.5220/0013312900003890
PB - SciTePress