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SHIFT: A Highly Realistic Financial Market Simulation Platform

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  • Thiago W. Alves
  • Ionut Florescu
  • George Calhoun
  • Dragos Bozdog

Abstract

This paper presents a new financial market simulator that may be used as a tool in both industry and academia for research in market microstructure. It allows multiple automated traders and/or researchers to simultaneously connect to an exchange-like environment, where they are able to asynchronously trade several financial assets at the same time. In its current iteration, this order-driven market implements the basic rules of U.S. equity markets, supporting both market and limit orders, and executing them in a first-in-first-out fashion. We overview the system architecture and we present possible use cases. We demonstrate how a set of automated agents is capable of producing a price process with characteristics similar to the statistics of real price from financial markets. Finally, we detail a market stress scenario and we draw, what we believe to be, interesting conclusions about crash events.

Suggested Citation

  • Thiago W. Alves & Ionut Florescu & George Calhoun & Dragos Bozdog, 2020. "SHIFT: A Highly Realistic Financial Market Simulation Platform," Papers 2002.11158, arXiv.org, revised Aug 2020.
    • Handle: RePEc:arx:papers:2002.11158
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    References listed on IDEAS

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    1. Sandrine Jacob Leal & Mauro Napoletano & Andrea Roventini & Giorgio Fagiolo, 2016. "Rock around the clock: An agent-based model of low- and high-frequency trading," Journal of Evolutionary Economics, Springer, vol. 26(1), pages 49-76, March.
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    Cited by:

    1. Thiago W. Alves & Ionuţ Florescu & Dragoş Bozdog, 2023. "Insights on the Statistics and Market Behavior of Frequent Batch Auctions," Mathematics, MDPI, vol. 11(5), pages 1-26, March.

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