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Financial black swans driven by ultrafast machine ecology

Author Info

Listed author(s):
  • Neil Johnson
  • Guannan Zhao
  • Eric Hunsader
  • Jing Meng
  • Amith Ravindar
  • Spencer Carran
  • Brian Tivnan
Registered author(s):

    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 (

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    File URL: http://arxiv.org/pdf/1202.1448
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    Paper provided by arXiv.org in its series Papers with number 1202.1448.

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    Date of creation: Feb 2012
    Handle: RePEc:arx:papers:1202.1448
    Contact details of provider: Web page: http://arxiv.org/

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    1. Lux, T. & M. Marchesi, "undated". "Scaling and Criticality in a Stochastic Multi-Agent Model of a Financial Market," Discussion Paper Serie B 438, University of Bonn, Germany, revised Jul 1998.
    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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    Cited by:

    1. 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.
    2. Mark Paddrik & Roy Hayes & William Scherer & Peter Beling, 2014. "Effects of Limit Order Book Information Level on Market Stability Metrics," Working Papers 14-09, Office of Financial Research, US Department of the Treasury.
    3. 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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