New Collectivity Measures for Financial Covariances and Correlations
Anton J. Heckens, Thomas Guhr

TL;DR
This paper introduces new measures for assessing collectivity in financial covariance and correlation matrices, revealing insights into market dynamics and identifying potential precursors to financial crises over a 30-year period.
Contribution
It proposes novel collectivity measures that distinguish systemic from sector-specific effects, enhancing the analysis of market structure and crisis precursors.
Findings
Identified collective signals around major financial crises.
Detected a potential precursor to the Lehman Brothers crash.
Observed fundamental changes in US market collectivity around 2015/2016.
Abstract
Complex systems are usually non-stationary and their dynamics is often dominated by collective effects. Collectivity, defined as coherent motion of the whole system or of some of its parts, manifests itself in the time-dependent structures of covariance and correlation matrices. The largest eigenvalue corresponds to the collective motion of the system as a whole, while the other large, isolated, eigenvalues indicate collectivity in parts of the system. In the case of finance, these are industrial sectors. By removing the collective motion of the system as a whole, the latter effects are much better revealed. We measure a remaining collectivity to which we refer as average sector collectivity. We identify collective signals around the Lehman Brothers crash and after the dot-com bubble burst. For the Lehman Brothers crash, we find a potential precursor. We analyze 213 US stocks over a…
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