Cite as:
Dion Harmon, Marcus A.M. de Aguiar, David D. Chinellato, Dan Braha, Irving Epstein, and Yaneer Bar-Yam, Predicting economic market crises using measures of collective panic, arXiv:1102.2620v1 (February 13, 2011).
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(also on arXiv)
Cite as:
Dion Harmon, Marco Lagi, Marcus A.M. de Aguiar, David D. Chinellato, Dan Braha, Irving Epstein, and Yaneer Bar-Yam, Anticipating economic market crises using measures of collective panic, PLoS ONE 10(7): e0131871 (July 2015), doi:10.1371/journal.pone.0131871
Abstract
Predicting panic is of critical importance in many areas of human and animal behavior, notably in the context of economics. The recent financial crisis is a case in point. Panic may be due to a specific external threat, or self-generated nervousness. Here we show that the recent economic crisis and earlier large single-day panics were preceded by extended periods of high levels of market mimicry --- direct evidence of uncertainty and nervousness, and of the comparatively weak influence of external news. High levels of mimicry can be a quite general indicator of the potential for self-organized crises.
Press Release: Researchers discover how to predict market crashes
Using new statistical analysis tools of complexity theory, researchers at the New England Complex Systems Institute (NECSI) performed new research on predicting market crashes.
It has long been thought that market crashes are triggered by panics that may or may not be justified by external news. This new research indicates that it is the internal structure of the market, not external crises, which is primarily responsible for crashes.
The number of different stocks that move up or down together is an indicator of the mimicry within the market, how much investors look to one another for cues. When the mimicry is high, many stocks follow each other's movements-a prime reason for panic to take hold.
NECSI researchers show that a dramatic increase in market mimicry occurred during the entire year before each market crash of the past 25 years, including the recent financial crisis.
"We have demonstrated mathematically that there is significant advance warning to provide a clear indicator of an impending [stock market] crash," explained Professor Yaneer Bar-Yam, president of NECSI and principal investigator on the research.
