Testing replication for an agent-based model of market fragmentation and latency arbitrage

Paper: arXiv 2604.20067

Authors: Ethan Ratliff-Crain, Colin M. Van Oort, Matthew T. K. Koehler, Brian F. Tivnan

Abstract

This study strengthens the foundations of multi-venue market modeling by attempting an independent replication of Wah and Wellman’s 2016 model of latency arbitrage in a fragmented market. We find that faithful replication is hindered by missing implementation details in the original paper and limited quantitative reporting. We demonstrate that increasing the number of simulation runs beyond the original design allows for the creation of bootstrap confidence intervals to support rigorous tests of quantitative alignment, compensating for lacking distributional information (e.g. variance). We also demonstrate that increased complexity across the modeled scenarios corresponds with increased difficulty aligning to the original results. We draw on a codebase released by the original authors in connection with a later paper to recover additional implementation details; however, we reject quantitative alignment between that codebase and the published results. Combining information from the paper and the released code, we achieve relational equivalence for most metrics but reject quantitative alignment for model settings where latency is non-zero. We show that many of the qualitative takeaways from the original paper on the effects of market fragmentation and latency arbitrage are sensitive to the specifics of a `greedy strategy’ extension given to the zero-intelligence (ZI) trader agents. Under an alternative interpretation of this strategy, we find that market fragmentation decreases execution times in all experiments and increases trader welfare in most experiments. Finally, to facilitate future replication, critique, and extension, we provide an ODD (Overview, Design concepts, Details) protocol for our implementations of the model.

Complexity vs Empirical Score

• Math Complexity: 3.5/10
• Empirical Rigor: 8.0/10
• Quadrant: Street Traders — practical and empirical, lighter on theory

Why this score: The research focuses on the empirical verification, replication, and sensitivity analysis of agent-based market models rather than dense mathematical derivations. Its rigorous attention to model alignment, statistical testing of simulation runs, and the provision of an ODD protocol demonstrates a high level of research engineering and implementation effort.

Research Flowchart

  flowchart TD
    A[<b>Research Goal:</b> Replication of Wah & Wellman's Latency Arbitrage Model] --> B[<b>Data & Inputs:</b> Original Paper & Authors' Subsequent Codebase]
    B --> C[<b>Computational Process:</b> Systematic Simulation with Increased Run Counts]
    C --> D[<b>Methodology:</b> Bootstrap CI Analysis & ODD Protocol Documentation]
    D --> E[<b>Finding 1:</b> Quantitative Divergence in Latency & Implementation Details]
    D --> F[<b>Finding 2:</b> Sensitivity of Qualitative Takeaways to 'Greedy Strategy' Logic]
    C --> G[<b>Outcome:</b> Relational Equivalence for Metrics; Framework for Future Critique]

Cited References (187)

1. Econophysics review: I . Empirical facts (2011) — link
2. Empirical game theoretic analysis: A survey (2025)
3. Theory Development Via Replicated Simulations and the Added Value of Standards (2020)
4. Advancing the art of simulation in the social sciences (1997)
5. A survey of agent-based modeling practices ( January 1998 to July 2008) (2009)
6. Making models match: Replicating an agent-based model (2007)
7. Stylized Facts (2008) — link
8. The Estimation of Leverage Effect With High - Frequency Data (2014) — link

1 of 187 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.