Queuing Uncertainty of Limit Orders

Limit orders submitted around the same time are subject to random latencies and will be queued accordingly. In equilibrium, end-of-queue limit orders always lose money—the liquidity supply appears excessive. The model generates empirical predictions regarding such “overshooting” liquidity: (i) new limit orders appear fleeting—clustered submissions are followed by immediate cancellations, (ii) the resulting cancel-to-add count ratio reflects adverse selection, and (iii) the cancel-to-add size ratio measures high-frequency market-making activity. Welfare can be hurt by the overshooting liquidity if it induces excessive speculation. Overall, the model contributes to a more comprehensive understanding and better utilization of order book data. This paper was accepted by Agostino Capponi, finance. Supplemental Material: The supplementary appendix and data files are available at https://doi.org/10.1287/mnsc.2023.03371 .

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Journal
Management Science
Published
2025-09-17
DOI
https://doi.org/10.1287/mnsc.2023.03371
Primary Topic
Economic theories and models
Type
article
Field-Weighted Citation Impact
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article

Queuing Uncertainty of Limit Orders

Bart Zhou Yueshen
Management Science
Economic theories and models
article

Queuing Uncertainty of Limit Orders

Bart Zhou Yueshen
article en

Abstract

Limit orders submitted around the same time are subject to random latencies and will be queued accordingly. In equilibrium, end-of-queue limit orders always lose money—the liquidity supply appears excessive. The model generates empirical predictions regarding such “overshooting” liquidity: (i) new limit orders appear fleeting—clustered submissions are followed by immediate cancellations, (ii) the resulting cancel-to-add count ratio reflects adverse selection, and (iii) the cancel-to-add size ratio measures high-frequency market-making activity. Welfare can be hurt by the overshooting liquidity if it induces excessive speculation. Overall, the model contributes to a more comprehensive understanding and better utilization of order book data. This paper was accepted by Agostino Capponi, finance. Supplemental Material: The supplementary appendix and data files are available at https://doi.org/10.1287/mnsc.2023.03371 .

Management Science
Singapore Management University (SG)
Openalex Percentile: Top 66%
Economic theories and models
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