Crisis Monitoring in Financial Sectors Using CAMEL Partial Triadic Analysis Model
This study presents the CAMEL Partial Triadic Analysis (CPTA) model, which combines CAMEL methodology with Partial Triadic Analysis (PTA) to evaluate financial indicators on a quarterly basis and delineate risk levels. By analyzing symmetries in data matrices and quantifying vector correlations, the...
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2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10838559/ |
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| author | Rody Guzman-Garzon Purificacion Galindo-Villardon Purificacion Vicente-Galindo |
| author_facet | Rody Guzman-Garzon Purificacion Galindo-Villardon Purificacion Vicente-Galindo |
| author_sort | Rody Guzman-Garzon |
| collection | DOAJ |
| description | This study presents the CAMEL Partial Triadic Analysis (CPTA) model, which combines CAMEL methodology with Partial Triadic Analysis (PTA) to evaluate financial indicators on a quarterly basis and delineate risk levels. By analyzing symmetries in data matrices and quantifying vector correlations, the model provides detailed insight into financial trends during recessionary periods, which is useful for financial regulators, public policy makers, and private banking institutions. The CPTA incorporates the commitment matrix, which synthesizes indicator values and provides stability in data matrices in adverse environments. Furthermore, the Fibonacci retracements technique was utilized to categorize variables, identify upward and downward trends, and estimate the solvency of each bank in relation to its respective segment. These results are contrasted using the HJ-Biplot and the dynamic HJ-Biplot, which allow for the evaluation of banking scenarios in the context of financial turbulence. When applied to the Ecuadorian banking sector, the model identified significant fluctuations in three key periods: pre-pandemic, pandemic, and the territorial crisis between Russia and Ukraine. Future research could extend the model by integrating all balance sheet variables against the base CPTA model through the application of Hidden Markov models. |
| format | Article |
| id | doaj-art-22d825e4e18e45c283ab8a9bc4e9ba43 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-22d825e4e18e45c283ab8a9bc4e9ba432025-01-28T00:01:40ZengIEEEIEEE Access2169-35362025-01-0113156501568210.1109/ACCESS.2025.352841210838559Crisis Monitoring in Financial Sectors Using CAMEL Partial Triadic Analysis ModelRody Guzman-Garzon0https://orcid.org/0000-0002-0471-3505Purificacion Galindo-Villardon1https://orcid.org/0000-0001-6977-7545Purificacion Vicente-Galindo2https://orcid.org/0000-0002-5854-273XDepartment of Statistics, University of Salamanca, Salamanca, SpainDepartment of Statistics, University of Salamanca, Salamanca, SpainDepartment of Statistics, University of Salamanca, Salamanca, SpainThis study presents the CAMEL Partial Triadic Analysis (CPTA) model, which combines CAMEL methodology with Partial Triadic Analysis (PTA) to evaluate financial indicators on a quarterly basis and delineate risk levels. By analyzing symmetries in data matrices and quantifying vector correlations, the model provides detailed insight into financial trends during recessionary periods, which is useful for financial regulators, public policy makers, and private banking institutions. The CPTA incorporates the commitment matrix, which synthesizes indicator values and provides stability in data matrices in adverse environments. Furthermore, the Fibonacci retracements technique was utilized to categorize variables, identify upward and downward trends, and estimate the solvency of each bank in relation to its respective segment. These results are contrasted using the HJ-Biplot and the dynamic HJ-Biplot, which allow for the evaluation of banking scenarios in the context of financial turbulence. When applied to the Ecuadorian banking sector, the model identified significant fluctuations in three key periods: pre-pandemic, pandemic, and the territorial crisis between Russia and Ukraine. Future research could extend the model by integrating all balance sheet variables against the base CPTA model through the application of Hidden Markov models.https://ieeexplore.ieee.org/document/10838559/CAMEL partial triadic analysis (CPTA)bankruptcy of banksfinancial crisesanalysis of three-way tablesSTATIS |
| spellingShingle | Rody Guzman-Garzon Purificacion Galindo-Villardon Purificacion Vicente-Galindo Crisis Monitoring in Financial Sectors Using CAMEL Partial Triadic Analysis Model IEEE Access CAMEL partial triadic analysis (CPTA) bankruptcy of banks financial crises analysis of three-way tables STATIS |
| title | Crisis Monitoring in Financial Sectors Using CAMEL Partial Triadic Analysis Model |
| title_full | Crisis Monitoring in Financial Sectors Using CAMEL Partial Triadic Analysis Model |
| title_fullStr | Crisis Monitoring in Financial Sectors Using CAMEL Partial Triadic Analysis Model |
| title_full_unstemmed | Crisis Monitoring in Financial Sectors Using CAMEL Partial Triadic Analysis Model |
| title_short | Crisis Monitoring in Financial Sectors Using CAMEL Partial Triadic Analysis Model |
| title_sort | crisis monitoring in financial sectors using camel partial triadic analysis model |
| topic | CAMEL partial triadic analysis (CPTA) bankruptcy of banks financial crises analysis of three-way tables STATIS |
| url | https://ieeexplore.ieee.org/document/10838559/ |
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