SynchronoGeometry in Financial Economics: A Phase-Based Theory of Systemic Risk and Financial Crises
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2026
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| author | SAMADI, SAADAT |
| author_facet | SAMADI, SAADAT |
| contents | <p>This study introduces <em>SynchronoGeometry</em>, a novel phase‑based framework for modeling systemic risk and predicting financial crises. Unlike conventional shock‑driven or balance‑sheet threshold approaches, the framework conceptualizes crises as endogenous states of maximal synchronization across financial institutions. We construct institution‑level financial phases from observable balance‑sheet and market data, embed them in a dynamic network, and model their interactions through stochastic phase dynamics. Systemic crises are identified using a composite, regulator‑consistent criterion that combines loss magnitude, contagion breadth, and interbank liquidity collapse. Empirically, the proposed Phase Synchronization Index (PSI) delivers early‑warning signals with lead times of 35–45 days and achieves AUROC values above 0.85, maintaining robustness across alternative network topologies and out‑of‑sample periods including the COVID‑19 shock. The framework unifies insights from financial cycles, network theory, and nonlinear dynamics, offering regulators a dynamic monitoring tool, a synchronization‑based stress‑testing complement, and a systemic‑importance ranking that extends beyond traditional size‑based metrics.</p> <p><strong>Keywords:</strong> Systemic Risk, Financial Crises, Synchronization, Financial Networks, Phase Dynamics, Early Warning Systems, Macroprudential Policy</p> <p><strong>JEL Codes:</strong> G01, G21, G28, C63</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18157375 |
| institution | Zenodo |
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| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | SynchronoGeometry in Financial Economics: A Phase-Based Theory of Systemic Risk and Financial Crises SAMADI, SAADAT <p>This study introduces <em>SynchronoGeometry</em>, a novel phase‑based framework for modeling systemic risk and predicting financial crises. Unlike conventional shock‑driven or balance‑sheet threshold approaches, the framework conceptualizes crises as endogenous states of maximal synchronization across financial institutions. We construct institution‑level financial phases from observable balance‑sheet and market data, embed them in a dynamic network, and model their interactions through stochastic phase dynamics. Systemic crises are identified using a composite, regulator‑consistent criterion that combines loss magnitude, contagion breadth, and interbank liquidity collapse. Empirically, the proposed Phase Synchronization Index (PSI) delivers early‑warning signals with lead times of 35–45 days and achieves AUROC values above 0.85, maintaining robustness across alternative network topologies and out‑of‑sample periods including the COVID‑19 shock. The framework unifies insights from financial cycles, network theory, and nonlinear dynamics, offering regulators a dynamic monitoring tool, a synchronization‑based stress‑testing complement, and a systemic‑importance ranking that extends beyond traditional size‑based metrics.</p> <p><strong>Keywords:</strong> Systemic Risk, Financial Crises, Synchronization, Financial Networks, Phase Dynamics, Early Warning Systems, Macroprudential Policy</p> <p><strong>JEL Codes:</strong> G01, G21, G28, C63</p> |
| title | SynchronoGeometry in Financial Economics: A Phase-Based Theory of Systemic Risk and Financial Crises |
| url | https://doi.org/10.5281/zenodo.18157375 |