Applications of Classifying Bidding Strategies for the CAT Tournament

  • Mark L. Gruman
  • Manjunath Narayana
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 44)


In the CAT Tournament, specialists facilitate transactions between buyers and sellers with the intention of maximizing profit from commission and other fees. Each specialist must find a well-balanced strategy that allows it to entice buyers and sellers to trade in its market while also retaining the buyers and sellers that are currently subscribed to it. Classification techniques can be used to determine the distribution of bidding strategies used by all traders subscribed to a particular specialist. Our experiments showed that Hidden Markov Model classification yielded the best results. The distribution of strategies, along with other competition-related factors, can be used to determine the optimal action in any given game state. Experimental data shows that the GD and ZIP bidding strategies are more volatile than the RE and ZIC strategies. An MDP framework for determining optimal actions given an accurate distribution of bidding strategies is proposed as a motivator for future work.


Hide Markov Model Markov Decision Process Conditional Random Field Bidding Strategy Total Trader 
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 2010

Authors and Affiliations

  • Mark L. Gruman
    • 1
  • Manjunath Narayana
    • 1
  1. 1.Department of Computer ScienceUniversity of MassachusettsAmherstUSA

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