Detecting Network Instability via Multiscale Detrended Cross-Correlations and MST Topology
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866918331848589312 |
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| author | Miranda, Jose De Leon Dolfin, Marina Kapetanios, George Leonida, Leone |
| author_facet | Miranda, Jose De Leon Dolfin, Marina Kapetanios, George Leonida, Leone |
| contents | We introduce a multiscale measure of network instability based on the joint use of Detrended Cross-Correlation Analysis (DCCA) and Minimum Spanning Tree (MST) filtering. The proposed metric, the Elastic Detrended Cross-Correlation Ratio (Elastic DCCR), is defined as a finite-difference measure of the logarithmic sensitivity of the average MST length to the observation scale. It captures how the structure of cross-correlation networks deforms across different investment horizons. When applied to a network of global equity indices, the Elastic DCCR rises sharply during episodes of financial stress, reflecting increased short-term coordination among investors and a contraction of correlation distances. The measure reveals scale-dependent reconfigurations in network topology that are not visible in single-scale analyses, and highlights clear differences between stressed and stable market regimes. The approach does not assume covariance stationarity and relies only on scale-dependent detrended correlations; as a result, it is broadly applicable to other complex systems in which interaction strength varies with scale. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2602_10174 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Detecting Network Instability via Multiscale Detrended Cross-Correlations and MST Topology Miranda, Jose De Leon Dolfin, Marina Kapetanios, George Leonida, Leone Physics and Society Econometrics 62P20 (Primary) 91G80, 60G18, 62M10 (Secondary) We introduce a multiscale measure of network instability based on the joint use of Detrended Cross-Correlation Analysis (DCCA) and Minimum Spanning Tree (MST) filtering. The proposed metric, the Elastic Detrended Cross-Correlation Ratio (Elastic DCCR), is defined as a finite-difference measure of the logarithmic sensitivity of the average MST length to the observation scale. It captures how the structure of cross-correlation networks deforms across different investment horizons. When applied to a network of global equity indices, the Elastic DCCR rises sharply during episodes of financial stress, reflecting increased short-term coordination among investors and a contraction of correlation distances. The measure reveals scale-dependent reconfigurations in network topology that are not visible in single-scale analyses, and highlights clear differences between stressed and stable market regimes. The approach does not assume covariance stationarity and relies only on scale-dependent detrended correlations; as a result, it is broadly applicable to other complex systems in which interaction strength varies with scale. |
| title | Detecting Network Instability via Multiscale Detrended Cross-Correlations and MST Topology |
| topic | Physics and Society Econometrics 62P20 (Primary) 91G80, 60G18, 62M10 (Secondary) |
| url | https://arxiv.org/abs/2602.10174 |