Skip to main content

Research Repository

Advanced Search

Speed traps: algorithmic trader performance under alternative market balances and structures

Peng, Yan; Shachat, Jason; Wei, Lijia; Zhang, S. Sarah

Speed traps: algorithmic trader performance under alternative market balances and structures Thumbnail


Authors

Yan Peng yan.peng2@durham.ac.uk
Combined Role

Lijia Wei

S. Sarah Zhang



Abstract

Using double auction market experiments with both human and agent traders, we demonstrate that agent traders prioritising low latency often generate, sometimes perversely so, diminished earnings in a variety of market structures and configurations. With respect to the benefit of low latency, we only find superior performance of fast-Zero Intelligence Plus (ZIP) buyers to human buyers in balanced markets with the same number of human and fast-ZIP buyers and sellers. However, in markets with a preponderance of agents on one side of the market and a noncompetitive market structure, such as monopolies and duopolies, fast-ZIP agents fall into a speed trap. In such speed traps, fast-ZIP agents capture minimal surplus and, in some cases, experience near first-degree price discrimination. In contrast, the trader performance of slow-ZIP agents is comparable to that of human counterparts, or even better in certain market conditions.

Citation

Peng, Y., Shachat, J., Wei, L., & Zhang, S. S. (2024). Speed traps: algorithmic trader performance under alternative market balances and structures. Experimental Economics, 27(2), 325-350. https://doi.org/10.1007/s10683-023-09816-8

Journal Article Type Article
Acceptance Date Nov 12, 2023
Online Publication Date Dec 8, 2023
Publication Date Apr 1, 2024
Deposit Date Nov 14, 2023
Publicly Available Date Jan 9, 2024
Journal Experimental Economics
Print ISSN 1386-4157
Electronic ISSN 1573-6938
Publisher Springer
Peer Reviewed Peer Reviewed
Volume 27
Issue 2
Pages 325-350
DOI https://doi.org/10.1007/s10683-023-09816-8
Keywords D40, Algorithmic trading, C78, Laboratory experiment, Speed, Trading agents, C92
Public URL https://durham-repository.worktribe.com/output/1928005

Files


Published Journal Article (Advance Online Version) (1.7 Mb)
PDF

Licence
http://creativecommons.org/licenses/by/4.0/

Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
This article is licensed under a Creative Commons Attribution 4.0 International License, which permits 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.






You might also like



Downloadable Citations