Latency arbitrage in fragmented markets: A strategic agent-based analysis

Elaine Wah () and Michael Wellman
Additional contact information
Elaine Wah: IEX Group, Inc., Postal: 4 World Trade Center, 44th Floor, New York, NY 10007, USA.

Algorithmic Finance, 2016, vol. 5, issue 3-4, 69-93

Abstract: We study the effect of latency arbitrage on allocative efficiency and liquidity in fragmented financial markets. We employ a simple model of latency arbitrage in which a single security is traded on two exchanges, with price quotes available to regular traders only after some delay. An infinitely fast arbitrageur reaps profits when the two markets diverge due to this latency in cross-market communication. Using an agent-based approach, we simulate interactions between high-frequency and zero-intelligence trading agents. From simulation data over a large space of strategy combinations, we estimate game models and compute strategic equilibria in a variety of market environments. We then evaluate allocative efficiency and market liquidity in equilibrium, and we find that market fragmentation and the presence of a latency arbitrageur reduces total surplus and negatively impacts liquidity. By replacing continuous-time markets with periodic call markets, we eliminate latency arbitrage opportunities and achieve further efficiency gains through the aggregation of orders over short time periods.

Keywords: High-frequency trading; latency arbitrage; agent-based simulation (search for similar items in EconPapers)
JEL-codes: C00 (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations: View citations in EconPapers (7)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ris:iosalg:0051

Access Statistics for this article

Algorithmic Finance is currently edited by Phil Maymin

More articles in Algorithmic Finance from IOS Press
Bibliographic data for series maintained by Saskia van Wijngaarden ( this e-mail address is bad, please contact ).