Treasury Auctions, Uniform or Discriminatory?: An Agent-Based Approach
AbstractThis study explores the use of the agent based computational economics (ACE) technique to address the question of how a Treasury should auction its securities. In particular, this study explores whether a Treasury should use a discriminatory-price rule. Buyers are modeled as profit seekers that are capable of submitting strategic bids via reinforcement learning. The buyers' profits are determined by auction prices and ex-post competitive resale prices. Experimental designs focus on four treatment varibles: (1) the buyers' learning representation; (2) market structures; (3) volatility of security prices in the secondary market; and (4) relative capacity (RCAP). Experimental findings show that security price volatility in the secondary market has little effect on market outcomes. However, market outcomes are sensitive to market structures, RCAP, and the buyers' learning representation. The two different auction rules result in different, persistent, systematically patterned market outcomes. Moreover, these findings help to explain why discrepancies have arisen among previous Treasury auction studies.
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Bibliographic InfoPaper provided by Iowa State University, Department of Economics in its series Staff General Research Papers with number 11988.
Date of creation: 23 Jun 2004
Date of revision:
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Postal: Iowa State University, Dept. of Economics, 260 Heady Hall, Ames, IA 50011-1070
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Web page: http://www.econ.iastate.edu
More information through EDIRC
agent-based computational economics; treasury auctions; discriminatory and unifome-price auction rules;
Find related papers by JEL classification:
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-06-27 (All new papers)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- James Nicolaisen & Valentin Petrov & Leigh Tesfatsion, 2000.
"Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing,"
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- Nicolaisen, James & Petrov, Valentin & Tesfatsion, Leigh S., 2001. "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing," Staff General Research Papers 2050, Iowa State University, Department of Economics.
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