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Low Financial Risk of Default and Productive Use of Assets Through Hidden Markov Models

Journal
Risks
ISSN
2227-9091
Date Issued
2025
Author(s)
Alexander Haro
Genaro Sandoval
María Rodríguez
Victor Armijo
Ivonne Arana
William Vasquez
Elizabeth Proaño
Martinez, Amanda  
Facultad de Ciencias Económicas, Administrativas y Negocios  
Type
journal-article
DOI
10.3390/risks13120230
URL
https://cris.indoamerica.edu.ec/handle/123456789/9891
Abstract
This paper analyzes solvency dynamics in Ecuador’s mutualist segment by modeling the joint behavior of the productive-assets-to-total-assets ratio (PATR) and portfolio-specific delinquency rates. Using monthly supervisory data from the Superintendencia de Economía Popular y Solidaria (SEPS) for the full universe of four mutualist institutions (2022–2025), we estimate a multivariate Gaussian Hidden Markov Model on system-level aggregates. The model identifies latent regimes that summarize configurations of asset productivity and segmented credit risk, distinguishing relatively sound conditions from episodes of heightened vulnerability. Model selection is based on information criteria, complemented by convergence checks, distributional diagnostics, and alternative covariance specifications to assess robustness. The approach is explicitly framed as diagnostic rather than causal or prescriptive: it does not replace simple thresholds nor calibrate capital buffers, but organizes supervisory information into interpretable solvency states with associated frequencies and expected durations. The framework is transparent and reproducible and provides a baseline for future extensions with longer samples and richer covariates.
Subjects

bank solvency

delinquency

finance

financial risk

financial system

hidden Markov models

machine learning

Investigación Indoamérica

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