A complexity gap computed as the normalized largest eigenvalue minus average pairwise correlation collapses to zero during shocks and shows a false-recovery phase before true restoration, predicting higher future volatility when low.
Sornette, Why stock markets crash: critical events in complex financial systems, Princeton university press, 2017
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Structural Dynamics of G5 Stock Markets During Exogenous Shocks: A Random Matrix Theory-Based Complexity Gap Approach
A complexity gap computed as the normalized largest eigenvalue minus average pairwise correlation collapses to zero during shocks and shows a false-recovery phase before true restoration, predicting higher future volatility when low.