@article{262812e163664fcab80bccb60dd5011f,
title = "Is liquidity provision informative? Evidence from agricultural futures markets",
abstract = "Electronic commodity trading witnesses a massive volume of order messages every trading day, but little is known about their informativeness. We examine limit order dynamics and their role in price discovery in the Chicago Mercantile Exchange (CME) corn, soybean, and wheat futures markets from January 2019 to June 2020, using order-level data. Between 75\% and 79\% of the large number of limit orders submitted are then deleted, which contrasts with the much smaller proportion getting executed or revised. Aggressive trades and limit orders substantially contribute to price discovery, whereas nonaggressive trades and limit orders, representing most market events, play a minor role. Following public information releases, there is a shift in trading strategies, with trades contributing more to price discovery and aggressive limit orders contributing less, compared to nonrelease days. Our findings suggest that most limit orders in agricultural futures markets continue to play the traditional role of uninformed liquidity provision.",
keywords = "futures markets, limit orders, liquidity, microstructure, price discovery",
author = "Ma, \{Richie R.\} and Teresa Serra",
note = "This work is a substantially revised version of Ma's Master thesis at the University of Illinois at Urbana\textbackslash{}u2010Champaign. We are grateful to Jesse Tack (the Editor), an Associate Editor, and three anonymous referees for their valuable comments and suggestions. We thank Philip Garcia, Lewen Guo, Scott Irwin, Sida Li, Hang Lin, Tianchen Zhao, seminar participants at the ACE Commercial Ag, and conference audience at 2023 NCCC\textbackslash{}u2010134, and American Finance Association 2024 Annual Meeting Ph.D. Poster Session for helpful discussions. An earlier version of this paper was circulated under the title \textbackslash{}u201CLimit orders and price discovery: Evidence from agricultural futures markets.\textbackslash{}u201D We gratefully acknowledge support from the National Institute of Food and Agriculture, the U.S. Department of Agriculture, under award \#ILLU\textbackslash{}u2010470\textbackslash{}u2010344, and the Office for Futures and Options Research at the UIUC. Ma acknowledges computational support from the Illinois Campus Cluster and high\textbackslash{}u2010performance computing nodes funded by the ACES College at the UIUC. The authors have signed nondisclosure agreements for the CME data used in this study. All access and use of CME data are subject to CME Data Terms of Use. We thank Matthew Frego of the CME for processing our CME data orders quickly and offering help when needed. Views expressed in this paper are those of the authors and do not necessarily reflect the views of the National Institute of Food and Agriculture and the U.S. Department of Agriculture. We have read American Journal of Agricultural Economics disclosure policy and have no conflicts of interest to disclose.",
year = "2025",
month = jan,
doi = "10.1111/ajae.12479",
language = "English (US)",
volume = "107",
pages = "125--151",
journal = "American Journal of Agricultural Economics",
issn = "0002-9092",
publisher = "John Wiley \& Sons, Ltd.",
number = "1",
}