Determining the banking solvency risk in times of COVID-19 through Gram-Charlier expansions
This paper proposes risk measures for bank solvency by accurately measuring the solvency risk components. These measures consider the minimum regulatory solvency levels and banks’ risk appetite level and risk profile. For this purpose, we used semi-nonparametric statistics to model stylized facts of...
- Autores:
-
Rendón, Juan F.
Cortés, Lina M.
Perote, Javier
- Tipo de recurso:
- Fecha de publicación:
- 2021
- Institución:
- Universidad EAFIT
- Repositorio:
- Repositorio EAFIT
- Idioma:
- eng
- OAI Identifier:
- oai:repository.eafit.edu.co:10784/30275
- Acceso en línea:
- http://hdl.handle.net/10784/30275
- Palabra clave:
- Solvency risk
Quantile Risk Metrics
Semi-nonparametric approach
Gram-Charlier expansions
COVID-19
- Rights
- License
- Acceso abierto
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Medellín de: Lat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degrees Long: 075 36 00 W degrees minutes Long: -75.6000 decimal degrees2021-09-21T21:48:57Z2021-09-202021-09-21T21:48:57Zhttp://hdl.handle.net/10784/30275C14C22C54G21G28This paper proposes risk measures for bank solvency by accurately measuring the solvency risk components. These measures consider the minimum regulatory solvency levels and banks’ risk appetite level and risk profile. For this purpose, we used semi-nonparametric statistics to model stylized facts of the risk distribution, particularly the high-order moments of the Solvency Decline Rate, the Tier Decline Rate, and the Portfolio Growth Rate variables. Additionally, these risk measures can be used to measure the risk of regulatory intervention and to define policies that establish the minimum solvency levels required by banking regulators by estimating the Quantile Risk Metrics. As a case study, we collected data on the solvency indicators of the Colombian banking system, which adapts to the standards established by the Basel Committee. According to the results, the liquidity injection measures implemented in response to the needs generated by the COVID-19 pandemic led to an increase in the levels of the risk portfolio in the Colombian banking system, which exceeded the 99th percentile of the probability distribution of monthly portfolio value changes.engUniversidad EAFITEscuela de Economía y FinanzasDetermining the banking solvency risk in times of COVID-19 through Gram-Charlier expansionsworkingPaperinfo:eu-repo/semantics/workingPaperDocumento de trabajo de investigacióndrafthttp://purl.org/coar/version/c_b1a7d7d4d402bccehttp://purl.org/coar/resource_type/c_8042Acceso abiertohttp://purl.org/coar/access_right/c_abf2Solvency riskQuantile Risk MetricsSemi-nonparametric approachGram-Charlier expansionsCOVID-19Rendón, Juan F.Cortés, Lina M.Perote, JavierInstituto Tecnológico Metropolitano - ITMUniversidad EAFITUniversity of SalamancaLICENSElicense.txtlicense.txttext/plain; charset=utf-82556https://repository.eafit.edu.co/bitstreams/1b83201c-7302-4e31-8cc9-a693d6e3e271/download76025f86b095439b7ac65b367055d40cMD51ORIGINALWP-2021-08-Lina Cortes.pdfWP-2021-08-Lina Cortes.pdfapplication/pdf1463587https://repository.eafit.edu.co/bitstreams/8d889f2e-1361-4973-b8dd-e453024a233c/download776f9e9e411ceb4ec76b79f0409a57dbMD5210784/30275oai:repository.eafit.edu.co:10784/302752024-03-05 14:06:12.892open.accesshttps://repository.eafit.edu.coRepositorio Institucional Universidad EAFITrepositorio@eafit.edu.co |
dc.title.eng.fl_str_mv |
Determining the banking solvency risk in times of COVID-19 through Gram-Charlier expansions |
title |
Determining the banking solvency risk in times of COVID-19 through Gram-Charlier expansions |
spellingShingle |
Determining the banking solvency risk in times of COVID-19 through Gram-Charlier expansions Solvency risk Quantile Risk Metrics Semi-nonparametric approach Gram-Charlier expansions COVID-19 |
title_short |
Determining the banking solvency risk in times of COVID-19 through Gram-Charlier expansions |
title_full |
Determining the banking solvency risk in times of COVID-19 through Gram-Charlier expansions |
title_fullStr |
Determining the banking solvency risk in times of COVID-19 through Gram-Charlier expansions |
title_full_unstemmed |
Determining the banking solvency risk in times of COVID-19 through Gram-Charlier expansions |
title_sort |
Determining the banking solvency risk in times of COVID-19 through Gram-Charlier expansions |
dc.creator.fl_str_mv |
Rendón, Juan F. Cortés, Lina M. Perote, Javier |
dc.contributor.author.none.fl_str_mv |
Rendón, Juan F. Cortés, Lina M. Perote, Javier |
dc.contributor.affiliation.spa.fl_str_mv |
Instituto Tecnológico Metropolitano - ITM Universidad EAFIT University of Salamanca |
dc.subject.keyword.spa.fl_str_mv |
Solvency risk Quantile Risk Metrics Semi-nonparametric approach Gram-Charlier expansions COVID-19 |
topic |
Solvency risk Quantile Risk Metrics Semi-nonparametric approach Gram-Charlier expansions COVID-19 |
description |
This paper proposes risk measures for bank solvency by accurately measuring the solvency risk components. These measures consider the minimum regulatory solvency levels and banks’ risk appetite level and risk profile. For this purpose, we used semi-nonparametric statistics to model stylized facts of the risk distribution, particularly the high-order moments of the Solvency Decline Rate, the Tier Decline Rate, and the Portfolio Growth Rate variables. Additionally, these risk measures can be used to measure the risk of regulatory intervention and to define policies that establish the minimum solvency levels required by banking regulators by estimating the Quantile Risk Metrics. As a case study, we collected data on the solvency indicators of the Colombian banking system, which adapts to the standards established by the Basel Committee. According to the results, the liquidity injection measures implemented in response to the needs generated by the COVID-19 pandemic led to an increase in the levels of the risk portfolio in the Colombian banking system, which exceeded the 99th percentile of the probability distribution of monthly portfolio value changes. |
publishDate |
2021 |
dc.date.available.none.fl_str_mv |
2021-09-21T21:48:57Z |
dc.date.issued.none.fl_str_mv |
2021-09-20 |
dc.date.accessioned.none.fl_str_mv |
2021-09-21T21:48:57Z |
dc.type.eng.fl_str_mv |
workingPaper info:eu-repo/semantics/workingPaper |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_b1a7d7d4d402bcce |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_8042 |
dc.type.local.spa.fl_str_mv |
Documento de trabajo de investigación |
dc.type.hasVersion.eng.fl_str_mv |
draft |
dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/10784/30275 |
dc.identifier.jel.none.fl_str_mv |
C14 C22 C54 G21 G28 |
url |
http://hdl.handle.net/10784/30275 |
identifier_str_mv |
C14 C22 C54 G21 G28 |
dc.language.iso.eng.fl_str_mv |
eng |
language |
eng |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.local.spa.fl_str_mv |
Acceso abierto |
rights_invalid_str_mv |
Acceso abierto http://purl.org/coar/access_right/c_abf2 |
dc.coverage.spatial.eng.fl_str_mv |
Medellín de: Lat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degrees Long: 075 36 00 W degrees minutes Long: -75.6000 decimal degrees |
dc.publisher.spa.fl_str_mv |
Universidad EAFIT |
dc.publisher.department.spa.fl_str_mv |
Escuela de Economía y Finanzas |
institution |
Universidad EAFIT |
bitstream.url.fl_str_mv |
https://repository.eafit.edu.co/bitstreams/1b83201c-7302-4e31-8cc9-a693d6e3e271/download https://repository.eafit.edu.co/bitstreams/8d889f2e-1361-4973-b8dd-e453024a233c/download |
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MD5 MD5 |
repository.name.fl_str_mv |
Repositorio Institucional Universidad EAFIT |
repository.mail.fl_str_mv |
repositorio@eafit.edu.co |
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1814110222090764288 |