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Financial black swans driven by ultrafast machine ecology

Author

Listed:
  • Neil Johnson
  • Guannan Zhao
  • Eric Hunsader
  • Jing Meng
  • Amith Ravindar
  • Spencer Carran
  • Brian Tivnan

Abstract

Society's drive toward ever faster socio-technical systems, means that there is an urgent need to understand the threat from 'black swan' extreme events that might emerge. On 6 May 2010, it took just five minutes for a spontaneous mix of human and machine interactions in the global trading cyberspace to generate an unprecedented system-wide Flash Crash. However, little is known about what lies ahead in the crucial sub-second regime where humans become unable to respond or intervene sufficiently quickly. Here we analyze a set of 18,520 ultrafast black swan events that we have uncovered in stock-price movements between 2006 and 2011. We provide empirical evidence for, and an accompanying theory of, an abrupt system-wide transition from a mixed human-machine phase to a new all-machine phase characterized by frequent black swan events with ultrafast durations (

Suggested Citation

  • Neil Johnson & Guannan Zhao & Eric Hunsader & Jing Meng & Amith Ravindar & Spencer Carran & Brian Tivnan, 2012. "Financial black swans driven by ultrafast machine ecology," Papers 1202.1448, arXiv.org.
  • Handle: RePEc:arx:papers:1202.1448
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    File URL: http://arxiv.org/pdf/1202.1448
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    References listed on IDEAS

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    1. repec:cup:cbooks:9780521819169 is not listed on IDEAS
    2. David Easley & Marcos M. López de Prado & Maureen O'Hara, 2012. "Flow Toxicity and Liquidity in a High-frequency World," Review of Financial Studies, Society for Financial Studies, vol. 25(5), pages 1457-1493.
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    Citations

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    Cited by:

    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. 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.
    3. repec:eee:dyncon:v:100:y:2019:i:c:p:200-229 is not listed on IDEAS
    4. Tobias Braun & Jonas A. Fiegen & Daniel C. Wagner & Sebastian M. Krause & Thomas Guhr, 2017. "Impact and Recovery Process of Mini Flash Crashes: An Empirical Study," Papers 1707.05580, arXiv.org.
    5. Sandrine Jacob Leal & Mauro Napoletano, 2016. "Market Stability vs. Market Resilience: Regulatory Policies Experiments in an Agent-Based Model with Low- and High- Frequency Trading," Sciences Po publications 2016-12, Sciences Po.
    6. repec:eee:jeborg:v:157:y:2019:i:c:p:15-41 is not listed on IDEAS
    7. Brian F. Tivnan & David Slater & James R. Thompson & Tobin A. Bergen-Hill & Carl D. Burke & Shaun M. Brady & Matthew T. K. Koehler & Matthew T. McMahon & Brendan F. Tivnan & Jason Veneman, 2018. "Price Discovery and the Accuracy of Consolidated Data Feeds in the U.S. Equity Markets," Papers 1810.11091, arXiv.org.
    8. David Rushing Dewhurst & Michael Vincent Arnold & Colin Michael Van Oort, 2018. "Selection mechanisms affect volatility in evolving markets," Papers 1812.05657, arXiv.org, revised Apr 2019.
    9. 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.
    10. Vasilios Mavroudis & Hayden Melton, 2019. "Libra: Fair Order-Matching for Electronic Financial Exchanges," Papers 1910.00321, arXiv.org.
    11. James Paulin & Anisoara Calinescu & Michael Wooldridge, 2018. "Understanding Flash Crash Contagion and Systemic Risk: A Micro-Macro Agent-Based Approach," Papers 1805.08454, arXiv.org.

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