research-article

Learning to classify and imitate trading agents in continuous double auction markets

Authors:

Mahmoud Mahfouz,

Manuela Veloso,

Danilo MandicAuthors Info & Claims

ICAIF '21: Proceedings of the Second ACM International Conference on AI in Finance

Article No.: 21, Pages 1 - 8

https://doi.org/10.1145/3490354.3494386

Published: 04 May 2022 Publication History

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.

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Cited By

Jiang SLi WSu QZhang X(2022)Deep Reinforcement Learning-Based Pricing Strategy in Double-Auction Market for Edge Computing Resource Allocation2022 International Conference on Networks, Communications and Information Technology (CNCIT)10.1109/CNCIT56797.2022.00017(52-61)Online publication date: Jun-2022
https://doi.org/10.1109/CNCIT56797.2022.00017

Index Terms

Learning to classify and imitate trading agents in continuous double auction markets
1. Applied computing
  1. Operations research
    1. Forecasting
2. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Supervised learning
        Supervised learning by classification
  2. Modeling and simulation
    1. Simulation types and techniques
      1. Discrete-event simulation

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cover image ACM Conferences

ICAIF '21: Proceedings of the Second ACM International Conference on AI in Finance

November 2021

450 pages

ISBN:9781450391481

DOI:10.1145/3490354

General Chairs:
Anisoara Calinescu
University of Oxford, UK
,
Lukasz Szpruch
The Alan Turing Institute and University of Edinburgh, UK

Copyright © 2021 ACM.

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Published: 04 May 2022

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ICAIF'21: 2nd ACM International Conference on AI in Finance

November 3 - 5, 2021

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Cited By

Jiang SLi WSu QZhang X(2022)Deep Reinforcement Learning-Based Pricing Strategy in Double-Auction Market for Edge Computing Resource Allocation2022 International Conference on Networks, Communications and Information Technology (CNCIT)10.1109/CNCIT56797.2022.00017(52-61)Online publication date: Jun-2022
https://doi.org/10.1109/CNCIT56797.2022.00017

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