RSS 1.0 Feed
RSS 2.0 Feed
Atom Feed
 

ZIP60: Further Explorations in the Evolutionary Design of Trader Agents and Online Auction-Market Mechanisms

Cliff, D. (2006) ZIP60: Further Explorations in the Evolutionary Design of Trader Agents and Online Auction-Market Mechanisms. IEEE Transactions on Evolutionary Computation . (Submitted)

Download

[img]
Preview
PDF
1543Kb

Abstract

The “ZIP” adaptive automated trading algorithm has been demonstrated to outperform human traders in experimental studies of continuous double auction (CDA) markets populated by mix¬tures of human and “software robot” traders. Previous papers have shown that values of the eight parameters governing behavior of ZIP traders can be automatically optimized using a genetic al¬gorithm (GA), and that markets populated by GA-optimized traders perform better than those populated by ZIP traders with manually-set parameter values. This paper introduces a more so¬phisticated version of the ZIP algorithm, called “ZIP60”, which requires the values of 60 pa¬rameters to be set correctly. ZIP60 is shown here to produce significantly better results in com¬parison to the original ZIP algorithm (called “ZIP8” hereafter) when a GA is used to search the 60-dimensional parameter space. It is also demonstrated here that this works best when the GA itself has control over the dimensionality of the search-space, allowing evolution to guide the expansion of the search-space up from 8 parameters to 60 via intermediate steps. Principal component analysis of the best evolved ZIP60 parameter-sets establishes that no ZIP8 solutions are em¬bedded in the 60-dimensional space. Moreover, some of the results and analysis presented here cast doubt on previously-published ZIP8 results concerning the evolution of new ‘hybrid’ auction mechanisms that appeared to be improvements on the CDA: it now seems likely that those results were actually consequences of the relative lack of sophistication in the original ZIP8 algorithm, because “hybrid” mechanisms occur much less frequently when ZIP60s are used.

Creators:Dave Cliff
Item Type:Article
Keywords:Algorithmic Trading; Automated Market Mechanism Design; Adaptive Trader-Agents; ZIP Traders; Genetic Algorithms; ZIP; ZIP60.
Research Group:Science and Engineering of Natural Systems
Deposited On:23 May 2007 by Cliff, David
Alternative Locations:http://www.ziptrader.org/zip60/zip60_full_final.pd...
ID Code:14078
Last Modified:23 Jan 2010 16:49
Citations:Google Scholar: 4

Tools

Metadata

Download Statistics

Last month

Last year

Members of ECS may view the download statistics dashboard for this record.

References in Article

Select the SEEK icon to attempt to find the referenced article. If it does not appear to be in this archive you will be forwarded to the paracite service. Poorly formated references will probably not work.

1. Aizawa, A. & Wah, B. (1994), “Scheduling of Genetic Algorithms in a Noisy Environment” Evolutionary Computation, 2(2):97–122.

2. Alexander, C. (2001), Market Models: A Guide to Financial Data Analysis. John Wiley.

3. Bagnall, A., & Toft, I. (2004), “Zero Intelligence Plus and Gjerstad-Dickhaut Agents for Sealed Bid Auctions” presented at Workshop on Trading Agent Design and Analysis (TADA04), New York, July 2004. (Preprint proceedings, pp.59–64), Available at http://www.eecs.harvard.edu/tada04/it-ajb-aamas04.pdf

4. Bagnall, A. & Toft, I. (2005) “Autonomous Adaptive Agents for Single-Seller Sealed Bid Auctions”, Autonomous Agents and Multi Agent Systems. In press.

5. Borgers, T. & Sarin, R. (1997), “Learning through reinforcement and replicator dynamics”, Journal of Economic Theory, 77: 1–14.

6. Bowling, M. & Veloso, M. (2004), "Existence of Multiagent Equilibria with Limited Agents", Journal of Artificial Intelligence Research 22:353-384,

7. Bullock, S. (1999), “Are artificial mutation biases unnatural?” in: Floreano, D., Nicoud, J.-D. & Mondada, F. (eds) Advances in Artificial Life: Fifth European Conference (ECAL99), pp. 64–73. Springer-Verlag.

8. Byde, A. (2003), “Applying Evolutionary Game Theory to Auction Mechanism Design”. Proceedings of the 2003 ACM Conference on E-Commerce. Also available as Hewlett-Packard Laboratories Technical Report HPL-2002-321.

9. Chatfield, C. & Collins, A. (1980), An Introduction to Multivariate Analysis. Chapman and Hall.

10. Clearwater, S., ed. (1995), Market-Based Control. World Scientific Press.

11. Cliff, D., Harvey, I., & Husbands, P. (1993), “Explorations in Evolutionary Robotics”, Adaptive Behavior, 2:73–110.

12. Cliff, D. (1997), “Minimal-intelligence agents for bargaining behaviours in market environments”. Hewlett-Packard Laboratories Technical Report HPL-97-91.

13. Cliff, D. (1998), “Genetic optimization of adaptive trading agents for double-auction markets” in Proceedings of Computational Intelligence in Financial Engineering (CIFEr), New York, 1998. IEEE/IAFE/Informs (preprint proceedings), pp.252–258, 1998.

14. Cliff, D. & Bruten, J. (1999), “Animat Market-Trading Interactions as Collective Social Adaptive Behavior''. Adaptive Behavior 7(3&4):385–414.

15. Cliff, D. (2001), “Evolutionary optimization of parameter sets for adaptive software-agent traders in continuous double-auction markets”. Presented at the Artificial Societies and Computational Markets (ASCMA98) workshop at the Second International Conference on Autonomous Agents, Minneapolis/St. Paul, May 1998. Also available as HP Labs Technical Report HPL-2001-99.

16. Cliff, D. (2002a), “Evolution of market mechanism through a continuous space of auction-types”. Presented at Computational Intelligence in Financial Engineering (CIFEr) session at Congress on Evolutionary Computation (CEC2002), Hawaii, May 2002.

17. Cliff, D. (2002b), “Evolution of market mechanism through a continuous space of auction-types II: Two-sided auction mechanisms evolve in response to market shocks”. Presented at Agents for Business Automation session at IC2002, Las Vegas, June 2002. In: Proceedings of the International Conference on Internet Computing IC02, Volume III, edited by H.R. Arabnia and Y. Mun. CSREA Press, pp.682–688.

18. Cliff, D. (2002c), “Visualizing Search-Spaces for Evolved Hybrid Auction Mechanisms”. Presented at the Beyond Fitness: Visualizing Evolution workshop at the 8th International Conference on the Simulation and Synthesis of Living Systems (ALifeVIII) conference, Sydney, December 2002. Also available as Hewlett-Packard Laboratories Technical Report HPL-2002-291.

19. Cliff, D. (2002d), “Evolution of Market Mechanism Through a Continuous Space of Auction-Types III: Multiple Market Shocks Give Convergence Toward CDA”. Hewlett-Packard Laboratories Technical Report HPL-2002-312.

20. Cliff, D., Walia, V., & Byde, A. (2002), “Evolved Hybrid Auction Mechanisms in Non-ZIP Trader Marketplaces”. Proceedings International Conference on Computational Intelligence for Financial Engineering (CIFEr03), Hong Kong, March 2003.

21. Cliff, D. (2003), Explorations in evolutionary design of online auction market mechanisms. Electronic Commerce Research and Applications 2(2):162–175, 2003.

22. Cliff, D. (2005), ZIP60: Further Explorations in the Evolutionary Design of Online Auction Market Mechanisms. Hewlett-Packard Laboratories Technical Report HPL-2005-85. Available from http://www.hpl.hp.com/techreports/2005/HPL-2005-85.pdf

23. Das, R., Hanson, J., Kephart, J., & Tesauro, G. (2001), “Agent-human interactions in the continuous double auction” Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI-01).

24. Easley, D., & Ledyard, J. (1992), “Theories of Price Formation and Exchange in Dou-ble Oral Auctions” in Friedman, D., & Rust, J. (editors) The Double Auction Market: Institutions, Theories, and Evidence, pp.63-97. Addison-Wesley;

25. Economist (2005), “The March of the Robo-Traders” The Economist Technology Quarterly, pp.23-24, 15 September 2005. Note: The Economist policy is to not identify the authors of their articles.

26. Feltovich, N. (2003), “Nonparametric tests of differences in medians: comparison of the Wilcoxon-Mann-Whitney and robust rank-order tests”, Experimental Economics, 6:273–297.

27. Feltovich, N. (Forthcoming 2006), “Critical values for the robust rank-order test”, forthcoming, Communications in Statistics.

28. Friedman, D. (1991), “A Simple Testable Model of Price Formation in the Double Auction Market”, Journal of Economic Behavior & Organization 15:47-70;.

29. Friedman, D., & Rust, J. (eds) (1993), The Double Auction Market: Institution, Theories, and Evidence. Addison Wesley

30. Gerding, E., Somefun, K., & La Poutré, H. (2004), “Multi-Attribute Bilateral Bargain¬ing in a One-to-Many Setting”, In Proceedings of the Workshop on Agent Medi¬ated Electronic Commerce VI (AMEC), New York, USA.

31. Gjerstad, S. & Dickhaut, J. (1998), “Price Formation in Double Auctions”, Games and Economic Behavior, 22:1–29.

32. Gode, D. & Sunder, S. (1993), “Allocative efficiency of markets with zero-intelligence traders”, Journal of Political Economy, 101:119–137.

33. Goldberg, D. (1989), Genetic Algorithms: In Search, Optimization, and Machine Learning. Reading, MA: Addison Wesley.

34. Gottlob, G., Greco, G., & Scarcello, F. (2005), "Pure Nash Equilibria: Hard and Easy Games", Journal of Artificial Intelligence Research, 24:57-406.

35. Graham-Rowe, D. (2005), “How Bots Can Earn More Than You Do”. New Scientist (20 Aug., 2005) 187(2513):26–27.

36. Greenwald, A., Guillemette, B., Naroditskiy, V., & Tschantz, M., (2005), “Scaling Up the Sample Average Approximation Method for Stochastic Optimization with Applications to Trading Agents” in Jansen, S. (ed) Working Notes from the IJCAI-05 Workshop on Trading Agent Design and Analysis (IJCAI05:TADA05). pp.21–27.

37. Harvey, I. (1994), The Artificial Evolution of Adaptive Behavior. PhD Thesis, School of Cognitive and Computing Sciences, University of Sussex, U.K.

38. He, M., Leung, H., & Jennings, N. (2003), "A fuzzy logic based bidding strategy for autonomous agents in continuous double auctions" IEEE Transactions on Knowledge and Data Engineering 15(6):1345–1363.

39. Hsieh, W. (2004), Nonlinear Multivariate and Time Series Analysis by Neural Network Methods. Review of Geophysics, 42(RG1003)1–25.

40. Jain, A., Murty, M. & Flynn, P. (1999), “Data Clustering: A Review”, ACM Computing Surveys, 31(3)264–323.

41. Koza, J. (1992), Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press.

42. Koza, J., Andre, D., Bennett, F., & Keane, M. (1998), Genetic Programming: Volume 3. Morgan Kauffman.

43. Ladley, D. & Bullock, S. (2005), “Who to listen to: Exploiting information quality in a ZIP-agent market” in Jansen, S. (ed) Working Notes from the IJCAI-05 Workshop on Trading Agent Design and Analysis (IJCAI05:TADA05). pp.28–34. Available from www.sics.se/tada05/tada05-proceedings.pdf.

44. Larrañaga, P. & Lozano, J. (eds) (2001), Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation. Kluwer.

45. Li, L. & Smith, S. (2004), "Speculation Agents for Dynamic, Multi-period Continuous Double Auctions in B2B Exchanges", Proceedings 37th Hawaii International Conference on System Sciences, Hawaii, January 2004.

46. Lochner, K. & Wellman, M. (2004), “Rule-Based Specification of Auction Mechanisms.” Proc. Third International Joint Conference on Autonomous Agents and Mul-tiagent Systems. pp.818-825.

47. Michalski, R. (2000), “Learnable Evolution Model: Evolutionary Processes Guided by Machine Learning”, Machine Learning, 38(1-2):9–40.

48. Mitchell, M. (1998), An Introduction to Genetic Algorithms. MIT Press.

49. NYSE New York Stock Exchange (2002), Stock Market Activity report available at: http://www.nyse.com/pdfs/02_STOCKMARKETACTIVITY.pdf

50. Pardoe, D. & Stone, P. (2005), “Developing Adaptive Auction Mechanisms”, ACM SIGecom Exchanges, 5(3):1–10.

51. Park, S., Durfee, E., & Birmingham, W. (2004), “Use of Markov Chains to Design an Agent Bidding Strategy for Continuous Double Auctions”, Journal of Artificial Intel-ligence Research (JAIR), 22: 175–214.

52. Phelps, S., McBurney, P., Parsons, S., & Sklar, E. (2002), “Co-evolutionary auction mechanism design: a Preliminary Report”, in J. Padget, O. Shehory, D. Parkes, N. Sadeh, & W. Walsh (Eds.): Agent-Mediated Electronic Commerce IV. Designing Mechanisms and Systems: AAMAS2002 Workshop on Agent-Mediated Electronic Commerce. Lecture Notes in Computer Science Vol. 2531; Springer-Verlag.

53. Phelps, S., Parsons, S., & McBurney, P. (2004), An Evolutionary Game-theoretic Comparision of Two Double Auction Market Designs. Presented at the Fourth International Workshop on Agent-Mediated Electronic Commerce (AMEC-IV). Available from http://ana.lcs.mit.edu/peyman/amec-vi-accepted.htm

54. Phelps, S., Marcinkuiewicz, M., Parsons, S., & McBurney, P. (2005), “Using Population-Based Search and Evolutionary Game Theory to Acquire Better-response Strategies for the Double Auction Market” in Jansen, S. (ed) Working Notes from the IJCAI-05 Workshop on Trading Agent Design and Analysis (IJCAI05:TADA05). pp.21–27. Available from http://www.sics.se/tada05/tada05-proceedings.pdf.

55. Preist, C. & van Tol, M. (1998), “Adaptive Agents in a Persistent-Shout Double Auc-tion”. Proceedings of ICE-98, ACM.

56. Pritchard, S. (2005), “Zippy Agents Going for Brokers”. Financial Times (London) FT-IT Review. July 13, 2005: p.2.

57. Qin, Z. (2002), Evolving Marketplace Designs by Artificial Agents. MSc Thesis, Computer Science Department, Bristol University, September 2002.

58. Qin, Z. & Kovacs, T. (2004), “Evolution of realistic hybrid auctions” In: Proceedings of the 2004 UK Workshop on Computational Intelligence (UKCI-04), pp.43–50. September 2004.

59. Reeves, D., Wellman, M., Mackie-Mason, J., & Osepayshvili, A. (2005), “Exploring Bidding Strategies for Market-Based Scheduling”, Decision Support Systems, 39:67–85.

60. Robinson, N. (2002), Evolutionary Optimization of Market-Based Control Systems for Resource Allocation in Compute Farms. MSc Thesis, School of Cognitive and Computing Sciences, University of Sussex, U.K.

61. Rothkopf, M., & Park, S. (2001), “An Elementary Introduction to Auctions”, Interfaces, 31:6(83–97).

62. Rumelhart, D., Hinton, G., & Williams, R. (1986), “Learning internal representations by error propagation”, in Parallel Distributed Processing: Explorations in the Micro-structures of Cognition, Volume 1, edited by D. Rumelhart and J. McClelland (Cambridge, MA: MIT Press), pp. 318–362.

63. Rust, J., Miller, J., & Palmer, R. (1992), “Behavior of trading automata in a computerized double auction market” in Friedman, D., & Rust, J. (editors) The Double Auction Market: Institutions, Theories, and Evidence, pp.155-198. Addison-Wesley;

64. Shipp, D. (2004), The effects of changes to supply and demand on trader agents and marketplaces. MSc Thesis, School of Computing, University of Leeds, UK.

65. Siegel, S., & Castellan, N. (1988), Nonparametric Statistics for the Behavioral Sciences. McGraw Hill.

66. Smith, V. (1962), “Experimental study of competitive market behavior” Journal of Political Economy, 70:111–137.

67. Stanley, K. & Miikkulainen, R. (2004), “Competitive Coevolution through Evolutionary Complexification”, Journal of Artificial Intelligence Research (JAIR), 21:63–100.

68. Stroud, P. (2001), “Kalman-Extended Genetic Algorithm for Search in Nonstationary Environments with Noisy Fitness Evaluations”. IEEE Transactions on Evolutionary Computation, 5(1):66–77.

69. Sun, J., Zhang, Q., & Tsang, E., (2005), “DE/EDA: A New Evolutionary Algorithm for Global Optimization, Information Sciences, 169(3):249–262.

70. Taylor, P., & Jonker, L., (1978), “Evolutionary Stable Strategies and Game Dynamics”, Mathematical Biosciences, 40:145-156.

71. Tesauro, G. & Das, R. (2001), “High-Performance Bidding Agents for the Continuous Double Auction”, presented at Economic Agents, Models, and Mechanisms Workshop, International Joint Conference on Artificial Intelligence (IJCAI), August 2001.

72. Tesauro, G. & Bredin, J. (2002), “Strategic Sequential Bidding in Auctions using Dynamic Programming”, Proceedings of the First International Conference on Autono-mous Agents and Multiagent Systems (AAMAS-02), Bologna, Italy.

73. Vytelingum, P., Dash, R., David, E., & Jennings, N. (2004), "A risk-based bidding strategy for continuous double auctions" Proceedings of the 16th European Confer-ence on Artificial Intelligence , Valencia , Spain, pp.79-83.

74. Walia, V. (2002), Evolving Market Design, MSc Thesis, School of Computer Science, University of Birmingham, UK.

75. Wellman, M., Reeves, D., Lochner, K., & Suri, R. (2005), “Searching for Walverine 2005” in Jansen, S. (ed) Working Notes from the IJCAI-05 Workshop on Trading Agent Design and Analysis (IJCAI05:TADA05). pp.1–6. Available from http://www.sics.se/tada05/tada05-proceedings.pdf.

76. Wichett, D. (2004), Coadaptive Dynamics of Minimal Intelligence Trading Agents in Competing Populations. MSc Thesis, Computer Science Dept, University of Birmingham, UK.

77. Wilson, R. (1987), "On Equilibria of Bid-Ask Markets" in Feiwel, G. (editor) Arrow and the Ascent of Modern Economic Theory, pp. 375-414. New York University Press.

78. Wilson, S. (1995), “Classifier Fitness Based on Accuracy” Evolutionary Computation, 3(2):149–175.

79. Witt, U. (1992), Evolutionary concepts in economics. Eastern Economic Journal, 18:405–419.

80. Wurman, P., Wellman, M., & Walsh, W. (2001), “A Parameterization of the Auction Design Space” Games and Economic Behavior, 35:304-338.

81. Zhang, Q., Sun, J., Tsang, E., & Ford, J. (2004), “Hybrid Estimation of Distribution Algorithm for Global Optimization”, Engineering Computations, 21(1):91–107.

Corrections

Repository Staff Only: item control page

  Welcome from Deputy Head of School (Research) Research Prospectus Industrial Partnerships New Research Students Notes for Guidance New Research Students Notes for Guidance
The ECS EPrints Repository supports OAI 2.0 with a base URL of http://eprints.ecs.soton.ac.uk/cgi/oai2

EPrints is free software developed by the University of Southampton to facilitate Open Access to research.
EPrints