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Multiagent System Simulations of Treasury Auctions

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Abstract

This study uses a multiagent system to determine which payment rule provides the most revenue in treasury auctions. The agents learn how to bid using straightforward bid adjustment rules that are based on impulse balance learning. The market model encompasses the when-issued, auction, and secondary markets, as well as bidding constraints for primary dealers. I find that when the number of primary bidders is less than 13 (Canada) the Discriminatory payment rule is revenue superior to the Uniform payment across most market price spreads. When the number of primary bidders is greater than 14 (United States), Uniform payment is revenue superior to Discriminatory payment for all market price spreads. In general, revenue increases with the minimum bid constraint and with the number of primary dealers for Uniform, Average, and Vickrey payment rules.

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  1. Department of Economics, University of Victoria, P.O. Box 1700, STN CSC, Victoria, BC, Canada, V8W 2Y2

    Alan Mehlenbacher

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  1. Alan Mehlenbacher
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Correspondence to Alan Mehlenbacher.

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Mehlenbacher, A. Multiagent System Simulations of Treasury Auctions. Comput Econ 34, 67–117 (2009). https://doi.org/10.1007/s10614-008-9165-z

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  • DOI: https://doi.org/10.1007/s10614-008-9165-z

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