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Using Evolutionary Game-Theory to Analyse the Performance of Trading Strategies in a Continuous Double Auction Market

  • Kai Cai
  • Jinzhong Niu
  • Simon Parsons
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4865)

Abstract

In agent-based computational economics, many different trading strategies have been proposed. Given the kinds of market that such trading strategies are employed in, it is clear that the performance of the strategies depends heavily on the behavior of other traders. However, most trading strategies are studied in homogeneous populations, and those tests that have been carried out on heterogeneous populations are limited to a small number of strategies. In this paper we extend the range of strategies that have been exposed to a more extensive analysis, measuring the performance of eight trading strategies using an approach based on evolutionary game theory.

Keywords

Nash Equilibrium Trading Strategy Dominant Strategy Payoff Matrix Replicator Dynamic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Kai Cai
    • 1
  • Jinzhong Niu
    • 1
  • Simon Parsons
    • 1
    • 2
  1. 1.Department of Computer Science, Graduate CenterCity University of New YorkNew York, NYUSA
  2. 2.Department of Computer and Information ScienceBrooklyn College, City University of New YorkBrooklynUSA

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