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Learning to Classify and Imitate Trading Agents in Continuous Double Auction Markets

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  • Mahmoud Mahfouz
  • Tucker Balch
  • Manuela Veloso
  • Danilo Mandic

Abstract

Continuous double auctions such as the limit order book employed by exchanges are widely used in practice to match buyers and sellers of a variety of financial instruments. In this work, we develop an agent-based model for trading in a limit order book and show (1) how opponent modelling techniques can be applied to classify trading agent archetypes and (2) how behavioural cloning can be used to imitate these agents in a simulated setting. We experimentally compare a number of techniques for both tasks and evaluate their applicability and use in real-world scenarios.

Suggested Citation

  • Mahmoud Mahfouz & Tucker Balch & Manuela Veloso & Danilo Mandic, 2021. "Learning to Classify and Imitate Trading Agents in Continuous Double Auction Markets," Papers 2110.01325, arXiv.org, revised Oct 2021.
    • Handle: RePEc:arx:papers:2110.01325
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    References listed on IDEAS

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    1. Mark Paddrik & Roy Hayes & William Scherer & Peter Beling, 2017. "Effects of limit order book information level on market stability metrics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 221-247, July.
    2. Mahmoud Mahfouz & Angelos Filos & Cyrine Chtourou & Joshua Lockhart & Samuel Assefa & Manuela Veloso & Danilo Mandic & Tucker Balch, 2019. "On the Importance of Opponent Modeling in Auction Markets," Papers 1911.12816, arXiv.org.
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