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Self-organised criticality in high frequency finance: the case of flash crashes

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  • Jeremy D. Turiel
  • Tomaso Aste

Abstract

With the rise of computing and artificial intelligence, advanced modeling and forecasting has been applied to High Frequency markets. A crucial element of solid production modeling though relies on the investigation of data distributions and how they relate to modeling assumptions. In this work we investigate volume distributions during anomalous price events and show how their tail exponents

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  • Jeremy D. Turiel & Tomaso Aste, 2021. "Self-organised criticality in high frequency finance: the case of flash crashes," Papers 2110.13718, arXiv.org.
    • Handle: RePEc:arx:papers:2110.13718
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    File URL: http://arxiv.org/pdf/2110.13718
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    Cited by:

    1. Turiel, Jeremy D. & Aste, Tomaso, 2022. "Heterogeneous criticality in high frequency finance: a phase transition in flash crashes," LSE Research Online Documents on Economics 113892, London School of Economics and Political Science, LSE Library.
    2. Antonio Briola & Silvia Bartolucci & Tomaso Aste, 2024. "Deep Limit Order Book Forecasting," Papers 2403.09267, arXiv.org, revised Mar 2024.

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