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Computational Economics

, 34:67 | Cite as

Multiagent System Simulations of Treasury Auctions

  • Alan Mehlenbacher
Article

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.

Keywords

Agent-based computational economics Multiagent systems Treasury auctions When-issued market Secondary market Primary dealers 

JEL Classifications

C15 C72 D83 

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Copyright information

© Springer Science+Business Media, LLC. 2008

Authors and Affiliations

  1. 1.Department of EconomicsUniversity of VictoriaVictoriaCanada

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