arXiv 8 Jun 2026 · physics.soc-ph
arXiv:2606.12460 · PDF · DOI · OpenAlex · Extracted main text
This paper studies sovereign stress avalanches and network amplification in Latin American credit markets using monthly J.P. Morgan EMBI Global Diversified spreads for eleven sovereigns over 2007-2026. Country stress events are defined as positive log-spread innovations exceeding country-specific volatility thresholds, and regional avalanches count the number of stressed countries in each month. The empirical design combines finite-sample power-law diagnostics, threshold robustness checks, a country-level reshuffling placebo, and rolling correlation, partial-correlation, and minimum-spanning-tree networks. Avalanche sizes are heavy-tailed, with an estimated exponent of 1.77, while spread changes and inter-event times lie in a heavy-tail boundary regime. The placebo shows synchronization far above independent stress timing, with p-values below 0.001. Large avalanches coincide with denser and more spectrally amplifying raw-correlation networks, but not after partial-correlation filtering, indicating common-factor co-movement rather than conditional regional propagation. Network metrics describe contemporaneous stress regimes rather than early-warning signals. The results provide a finite-size criticality framework for monitoring sovereign fragility in emerging markets.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Stumpf, Michael P. H. and Porter, Mason A (2012) Critical Truths about Power Laws | 1.000 | 7 | 6 | 100% |
| 2 | Forbes, Kristin J. and Rigobon, Roberto (2002) No Contagion, Only Interdependence: Measuring Stock Market Comovements | 1.000 | 6 | 5 | 100% |
| 3 | Clauset, Aaron and Shalizi, Cosma Rohilla and Newman, M. E. J (2009) Power-Law Distributions in Empirical Data | 1.000 | 5 | 4 | 100% |
| 4 | Bak, Per and Tang, Chao and Wiesenfeld, Kurt (1987) Self-Organized Criticality: An Explanation of the 1/f Noise | 0.843 | 3 | 3 | 100% |
| 5 | Bak, Per and Tang, Chao and Wiesenfeld, Kurt (1988) Self-Organized Criticality | 0.843 | 3 | 3 | 100% |
| 6 | Bak, Per (1996) How Nature Works: The Science of Self-Organized Criticality | 0.843 | 3 | 3 | 100% |
| 7 | Tumminello, Michele and Aste, Tomaso and Di Matteo, Tiziana and Mant… (2005) A Tool for Filtering Information in Complex Systems | 0.843 | 3 | 3 | 100% |
| 8 | Vuong, Quang H (1989) Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses | 0.843 | 3 | 3 | 100% |
| 9 | Acemoglu, Daron and Carvalho, Vasco M. and Ozdaglar, Asuman and Tahb… (2012) The Network Origins of Aggregate Fluctuations | 0.644 | 2 | 2 | 100% |
| 10 | Bak, Per and Chen, Kan and Scheinkman, José and Woodford, Michael (1993) Aggregate Fluctuations from Independent Sectoral Shocks: Self-Organized Criticality in a Model of Production and Inventory Dynam… | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 42 scored citations.