Financial black swans driven by ultrafast machine ecology

TL;DR

This paper investigates ultrafast black swan events in financial markets, revealing a transition to an all-machine phase with frequent, rapid crashes, and offers a theory linking systemic fluctuations to system ecology and information processing.

Contribution

It uncovers and models the dynamics of ultrafast black swan events, providing empirical evidence and a theoretical framework for understanding systemic risks in high-speed socio-technical systems.

Findings

Identified 18,520 ultrafast black swan events in stock markets (2006-2011).

Detected a phase transition to an all-machine system with frequent ultrafast events.

Major international banks are most susceptible to ultrafast systemic disruptions.

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 (<650ms for crashes, <950ms for spikes). Our theory quantifies the systemic fluctuations in these two distinct phases in terms of the diversity of the system's internal ecology and the amount of global information being processed. Our finding that the ten most susceptible entities are major international banks, hints at a hidden relationship between these ultrafast 'fractures' and the slow 'breaking' of the global financial system post-2006. More generally, our work provides tools to help predict and mitigate the systemic risk developing in any complex socio-technical system that attempts to operate at, or beyond, the limits of human response times.