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An agent-based model and detect price manipulation based on intraday transaction data with simulation

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  • Mohammad Zare
  • Omid Naghshineh A.
  • Erfan Salavati
  • Adel Mohammadpour

Abstract

In this article, we propose an agent-based model for LOB markets, and by simulation, we estimate the model’s parameters. This model has two interesting points. First, we divide the data transaction of 1 day into six parts. Second, we detect price manipulation by using intraday transaction data. To detect price manipulation, we simulate the model once without the price manipulator and once with the price manipulator, and then by using some statistical properties such as skewness we find relations to detect price manipulation.

Suggested Citation

  • Mohammad Zare & Omid Naghshineh A. & Erfan Salavati & Adel Mohammadpour, 2021. "An agent-based model and detect price manipulation based on intraday transaction data with simulation," Applied Economics, Taylor & Francis Journals, vol. 53(43), pages 4931-4949, September.
    • Handle: RePEc:taf:applec:v:53:y:2021:i:43:p:4931-4949
    DOI: 10.1080/00036846.2021.1912282
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    References listed on IDEAS

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    Cited by:

    1. Prashant Priyadarshi & Prabhat Kumar, 2024. "A comprehensive review on insider trading detection using artificial intelligence," Journal of Computational Social Science, Springer, vol. 7(2), pages 1645-1664, October.

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