Article

High-performance bidding agents for the continuous double auction

Authors:

Gerald Tesauro,

Rajarshi DasAuthors Info & Claims

EC '01: Proceedings of the 3rd ACM conference on Electronic Commerce

Pages 206 - 209

https://doi.org/10.1145/501158.501183

Published: 14 October 2001 Publication History

Get Access

Abstract

We develop two bidding algorithms for real-time Continuous Double Auctions (CDAs) using a variety of market rules that offer what we believe to be the strongest known performance of any published bidding strategy. Our algorithms are based on extensions of the "ZIP" (Cliff, 1997) and "GD" (Gjerstad and Dickhaut, 1998) strategies: we have made essential modifications to these strategies which enable trading multiple units in real-time markets. We test these strategies against each other and against the sniping strategy of (Rust et al., 1992) and the baseline "Zero Intelligence" strategy of (Gode and Sunder, 1992), using both a discrete-time simulator and a genuine real-time multi-agent environment called MAGENTA (Das et al., 2001). Under various market rules and limit price distributions, our modified Gjerstad-Dickhaut ("MGD") strategy outperforms the original GD, and generally ominates the other strategies.

References

[1]

J. Andreoni and J. Miller. Auctions with artificial adaptive agents. Games and Economic Behavior', 10:3964, 1995.

Google Scholar

[2]

D. Cliff. Minimal-intelligence agents for bargaining behaviors in market-based environments. Technical Report HPL-97-91, Hewlett Packard Labs., 1997.

Google Scholar

[3]

R. Das, J. E. Hanson, J. O. Kephart, and G. Tesauro. Agent-human interactions in the continuous double auction. In Proceedings of L}CAI-01, San Francisco, CA, 2001. Morgan Kaufmann.

Digital Library

Google Scholar

[4]

S. Gjerstad and J. Dickhaut. Price formation in double auctions. Games and Economic Behavior, 22:129, 1998.

Crossref

Google Scholar

[5]

D. Gode and S. Sunder. Allocative efficiency of markets with zero intellegence traders: Market as a partial substitute for individual rationality. J. of Political Economy, 101:119137, 1993.

Crossref

Google Scholar

[6]

C. Preist and M. van Tol. Adaptive agents in a persistent shout double auction. In Proceedings of ICE-98. ACM, 1998.

Digital Library

Google Scholar

[7]

J. Rust, J. Miller, and R. Palmer. Behavior of trading automata in a computerized double auction market. In D. Friedman and J. Rust, editors, The Double Auction Market: Institutions, Theories, and Evidence, Redwood City, CA, 1992. Addison-Wesley.

Google Scholar

[8]

J. Rust, J. Miller, and R. Palmer. Characterizing effective trading strategies: Insights from the computerized double auction tournament. J. of Economic Dynamics and Control, 18:6196, 1994.

Crossref

Google Scholar

[9]

V. L. Smith. An experimental study of competitive market behavior. J. of Political Economy, 70:111137, 1962.

Crossref

Google Scholar

[10]

V. L. Smith. Microeconomic systems as an experimental science. American Economic Review, 72:923 955, 1982.

Google Scholar

Cited By

View all

Liu YSun SShen GWang XWang L(2025)Designing a double auction mechanism for parallel machines scheduling with multiple consumer agents and resource agentsExpert Systems with Applications10.1016/j.eswa.2024.126275268(126275)Online publication date: Apr-2025
https://doi.org/10.1016/j.eswa.2024.126275
Varosyan A(2024)Distributed Multi-Agent Stock Exchange Environment for Investigating Arbitrage and Price ConvergenceSSRN Electronic Journal10.2139/ssrn.4893697Online publication date: 2024
https://doi.org/10.2139/ssrn.4893697
Bokhari ACliff D(2024)Exploring Narrative Economics: An Agent-Based Co-Evolutionary Model Featuring Nonlinear Continuous-Time Opinion DynamicsAgents and Artificial Intelligence10.1007/978-3-031-55326-4_19(387-410)Online publication date: 15-Mar-2024
https://doi.org/10.1007/978-3-031-55326-4_19
Show More Cited By

Index Terms

High-performance bidding agents for the continuous double auction
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
      1. Multi-agent systems
    2. Search methodologies
      1. Heuristic function construction
2. Mathematics of computing
  1. Discrete mathematics
    1. Combinatorics
      1. Combinatorial algorithms

Recommendations

Reputation-aware continuous double auction
AAAI'14: Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence

Truthful bidding is a desirable property for continuous double auctions (CDAs). Many incentive mechanisms have been proposed to elicit truthful bids. However, existing truthful CDA mechanisms often overlook the possibility that sellers may choose not to ...
Bidding strategy for agents in multi-attribute combinatorial double auction

Effective bidding in multi-attribute combinatorial double auction is complex.A traded package in the history of the market does not reveal any unit price of the items.Bidders should predict their true desired combination and quantity of items.The ...
Strategic bidding in continuous double auctions

In this paper, we describe a novel bidding strategy that autonomous trading agents can use to participate in Continuous Double Auctions (CDAs). Our strategy is based on both short and long-term learning that allows such agents to adapt their bidding ...

Comments

Information & Contributors

Information

Published In

EC '01: Proceedings of the 3rd ACM conference on Electronic Commerce

October 2001

277 pages

ISBN:1581133871

DOI:10.1145/501158

Conference Chairs:
Michael P. Wellman
University of Michigan
,
Yoav Shoham
Stanford University

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 October 2001

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Qualifiers

Article

Conference

EC01

Sponsor:

SIGecom

EC01: Third ACM Conference on Electronic Commerce

October 14 - 17, 2001

Florida, Tampa, USA

Acceptance Rates

EC '01 Paper Acceptance Rate 35 of 100 submissions, 35%;

Overall Acceptance Rate 664 of 2,389 submissions, 28%

Upcoming Conference

EC '25

Sponsor:
sigecom

The 25th ACM Conference on Economics and Computation

July 7 - 11, 2025

Stanford , CA , USA

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

72
Total Citations
View Citations
953
Total Downloads

Downloads (Last 12 months)15
Downloads (Last 6 weeks)3

Reflects downloads up to 06 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Liu YSun SShen GWang XWang L(2025)Designing a double auction mechanism for parallel machines scheduling with multiple consumer agents and resource agentsExpert Systems with Applications10.1016/j.eswa.2024.126275268(126275)Online publication date: Apr-2025
https://doi.org/10.1016/j.eswa.2024.126275
Varosyan A(2024)Distributed Multi-Agent Stock Exchange Environment for Investigating Arbitrage and Price ConvergenceSSRN Electronic Journal10.2139/ssrn.4893697Online publication date: 2024
https://doi.org/10.2139/ssrn.4893697
Bokhari ACliff D(2024)Exploring Narrative Economics: An Agent-Based Co-Evolutionary Model Featuring Nonlinear Continuous-Time Opinion DynamicsAgents and Artificial Intelligence10.1007/978-3-031-55326-4_19(387-410)Online publication date: 15-Mar-2024
https://doi.org/10.1007/978-3-031-55326-4_19
Cliff D(2023)Parameterised response zero intelligence tradersJournal of Economic Interaction and Coordination10.1007/s11403-023-00388-719:3(439-492)Online publication date: 30-May-2023
https://doi.org/10.1007/s11403-023-00388-7
Chowdhury MKiekintveld CSon TPontelli E(2023)SPOT: Strategies for Power Trading in Wholesale Electricity MarketsEnergy Sustainability through Retail Electricity Markets10.1007/978-3-031-39707-3_8(145-170)Online publication date: 26-Jul-2023
https://doi.org/10.1007/978-3-031-39707-3_8
Cliff DZhang ZTaylor N(2022)Adding Supply/Demand Imbalance-Sensitivity to Simple Automated Trader-AgentsAgents and Artificial Intelligence10.1007/978-3-031-10161-8_15(269-293)Online publication date: 19-Jul-2022
https://doi.org/10.1007/978-3-031-10161-8_15
Alexandrov NCliff DFiguero C(2022)Exploring Coevolutionary Dynamics Between Infinitely Diverse Heterogenous Adaptive Automated Trading AgentsAdvances in Social Simulation10.1007/978-3-030-92843-8_8(93-104)Online publication date: 30-Mar-2022
https://doi.org/10.1007/978-3-030-92843-8_8
Wang XHoang CVorobeychik YWellman M(2021)Spoofing the Limit Order Book: A Strategic Agent-Based AnalysisGames10.3390/g1202004612:2(46)Online publication date: 24-May-2021
https://doi.org/10.3390/g12020046
March C(2021)Strategic interactions between humans and artificial intelligence: Lessons from experiments with computer playersJournal of Economic Psychology10.1016/j.joep.2021.10242687(102426)Online publication date: Dec-2021
https://doi.org/10.1016/j.joep.2021.102426
Hanifan HWatson BCartlidge JCliff D(2021)Time Matters: Exploring the Effects of Urgency and Reaction Speed in Automated TradersAgents and Artificial Intelligence10.1007/978-3-030-71158-0_7(149-170)Online publication date: 14-Mar-2021
https://doi.org/10.1007/978-3-030-71158-0_7
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Reputation-aware continuous double auction

Bidding strategy for agents in multi-attribute combinatorial double auction

Strategic bidding in continuous double auctions