<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0121-750X</journal-id>
<journal-title><![CDATA[Ingeniería]]></journal-title>
<abbrev-journal-title><![CDATA[ing.]]></abbrev-journal-title>
<issn>0121-750X</issn>
<publisher>
<publisher-name><![CDATA[Universidad Distrital Francisco José de Caldas]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0121-750X2022000100203</article-id>
<article-id pub-id-type="doi">10.14483/23448393.18575</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Capital Requirements to Cover Operational Risk in Financial Institutions of Emerging Markets A Gaussian Copula Model]]></article-title>
<article-title xml:lang="es"><![CDATA[Requerimientos de capital para cubrir el riesgo operativo en instituciones financieras de mercados emergentes. Un modelo de Cópula Gaussiana]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Garzón-Rozo]]></surname>
<given-names><![CDATA[Betty Johanna]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Martín-Bernal]]></surname>
<given-names><![CDATA[Claudia Paola]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Rueda-Velasco]]></surname>
<given-names><![CDATA[Feizar]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,The University of Edinburgh  ]]></institution>
<addr-line><![CDATA[Edinburgh UK]]></addr-line>
<country>United Kingdom</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Banco de la República  ]]></institution>
<addr-line><![CDATA[Bogotá ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad Distrital Francisco José de Caldas  ]]></institution>
<addr-line><![CDATA[Bogotá ]]></addr-line>
<country>Colombia</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>04</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>04</month>
<year>2022</year>
</pub-date>
<volume>27</volume>
<numero>1</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0121-750X2022000100203&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0121-750X2022000100203&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0121-750X2022000100203&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract  Context:  Advanced Measurement Approach (AMA) has been the umbrella to identify the models used for modeling the capital to cover Operational Risk (Total Operational Value at Risk, OpVaR) in financial institutions in developed countries. The Loss Distribution Approach (LDA) has been the most popular model used by international banks for OpVaR calculation. However, operational losses often have multivariate dependences that are not accounted for in the LDA. This paper applies a Gaussian copula to model the multivariate dependences in operational losses.  Method:  Two models were compared to estimate capital requirement for operational risk. Model (i) is the standard LDA model (BCBS 2004). Model (ii) incorporates a multivariate Gaussian copula into the LDA to model multivariate dependence between operational losses (severities). This research analyzes an operational loss data set, SAS® Operational Risk Global Data (SAS OpRisk Global Data), in order to model operational risk at financial institutions in emerging markets between 1990 and 2013.  Results: The impact of Model (ii) was evaluated on the estimates of the total regulatory capital for operational risk and compared with the one predicted by (i). The results confirm the existence of diversification benefit up to 33 %.  Conclusions:  Modeling explicitly the multivariate dependence between operational losses has a clear impact on capital requirement for institutions in emerging markets. The implementation of a Gaussian copula into the LDA model provides a sophisticated tool to estimate operational risk capital in emerging markets, as well as the possibility for diversification benefit.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen  Contexto:  Bajo el Enfoque de Medición Avanzada (AMA) se han identificado los modelos utilizados para modelar el capital necesario para cubrir el Riesgo Operacional (Valor Operacional Total del Riesgo, OpVaR) en instituciones financieras de países desarrollados. El Enfoque de Distribución de Pérdida (LDA) ha sido el modelo más popular usado por bancos internacionales para calcular el OpVaR. Sin embargo, las pérdidas operacionales suelen tener dependencias multivariadas que no son tenidas en cuenta en el LDA. Este artículo aplica una cópula Gaussiana para modelar las dependencias multivariadas en pérdidas operacionales.  Método:  Se compararon dos modelos para estimar el requerimiento de capital para el riesgo operacional. El Modelo (i) es el modelo estándar LDA (BCBS 2004). El Modelo (ii) incorpora una copula Gaussiana al LDA para modelar la dependencia multivariada entre pérdidas operacionales (severidades). Para modelar el riesgo operacional en instituciones financieras de mercados emergentes, se emplearon datos reales de perdidas operacionales entre 1990 y 2013 provistas por SAS® Operational Risk Global Data (SAS OpRisk Global Data).  Resultados:  El impacto del Modelo (ii) se evaluó con respecto a los estimados del capital total regulatorio para el riesgo operacional y se comparó con el predicho por (i). Los resultados confirman la existencia de un beneficio de diversificación de hasta 33 %.  Conclusiones: Modelar explícitamente la dependencia multivariada entre pérdidas operacionales tiene un claro impacto sobre el requerimiento de capital para instituciones financieras en mercados emergentes. La implementación de la cópula Gaussiana en el modelo LDA provee una herramienta sofisticada para estimar el capital de riesgo operacional en mercados emergentes, así como la posibilidad de obtener beneficio por diversificación.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[operational risk]]></kwd>
<kwd lng="en"><![CDATA[Loss Distribution Approach (LDA)]]></kwd>
<kwd lng="en"><![CDATA[multivariate copulas]]></kwd>
<kwd lng="en"><![CDATA[emerging markets.]]></kwd>
<kwd lng="es"><![CDATA[riesgo operativo]]></kwd>
<kwd lng="es"><![CDATA[Modelo de Distribución de Pérdidas Agregadas (LDA)]]></kwd>
<kwd lng="es"><![CDATA[cópulas multivariadas]]></kwd>
<kwd lng="es"><![CDATA[mercados emergentes.]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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