Jose De Leon Miranda
Jose De Leon Miranda has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
George Kapetanios
2 shared publications- Leone Leonida
King’s Business School, King’s College London, 30 Aldwych, WC2B 4BG, London, United Kingdom
2 shared publications - Marina Dolfin
King’s Business School, King’s College London, 30 Aldwych, WC2B 4BG, London, United Kingdom
2 shared publications
Latest Publications
- Open Access
- 25 July 2026
- Published by Elsevier in Physica A: Statistical Mechanics and its Applications
- Vol. 699
Detecting scale-dependent network reconfiguration via multiscale detrended cross-correlations and MST topology
- 25 July 2026
- Published by Elsevier in Physica A: Statistical Mechanics and its Applications
- Vol. 699
Open AccessDetecting scale-dependent network reconfiguration via multiscale detrended cross-correlations and MST topology
- Open Access
- 24 March 2026
- Published by Elsevier in SSRN Electronic Journal
Detecting Network Instability via Multiscale Detrended Cross-Correlations and MST Topology
We introduce a multiscale measure of network instability based on the joint use ofDetrended 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 duringepisodes of financial stress, reflecting increased short-term coordination amonginvestors and a contraction of correlation distances. The measure reveals scale-dependent reconfigurations in network topology thatare not visible in single-scale analyses, and highlights clear differencesbetween 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.
- 24 March 2026
- Published by Elsevier in SSRN Electronic Journal
Open AccessDetecting Network Instability via Multiscale Detrended Cross-Correlations and MST Topology
We introduce a multiscale measure of network instability based on the joint use ofDetrended 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 duringepisodes of financial stress, reflecting increased short-term coordination amonginvestors and a contraction of correlation distances. The measure reveals scale-dependent reconfigurations in network topology thatare not visible in single-scale analyses, and highlights clear differencesbetween 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.