Está Vd. en

Documento DOUE-L-2024-80144

Reglamento Delegado (UE) 2024/397 de la Comisión, de 20 de octubre de 2023, por el que se completa el Reglamento (UE) nº 575/2013 del Parlamento Europeo y del Consejo en lo que respecta a las normas técnicas de regulación relativas al cálculo de la medida del riesgo en un supuesto de tensión.

Publicado en:
«DOUE» núm. 397, de 29 de enero de 2024, páginas 1 a 21 (21 págs.)
Departamento:
Unión Europea
Referencia:
DOUE-L-2024-80144

TEXTO ORIGINAL

 

LA COMISIÓN EUROPEA,

Visto el Tratado de Funcionamiento de la Unión Europea,

Visto el Reglamento (UE) n.o 575/2013 del Parlamento Europeo y del Consejo, de 26 de junio de 2013, sobre los requisitos prudenciales de las entidades de crédito, y por el que se modifica el Reglamento (UE) n.o 648/2012 (1), y en particular su artículo 325 ter duodecies, apartado 3, párrafo cuarto,

Considerando lo siguiente:

(1)

Con el fin de garantizar la igualdad de condiciones de competencia entre las entidades de la Unión y reducir al mínimo el arbitraje regulador, las metodologías para determinar supuestos extremos de perturbación futura en relación con los factores de riesgo no modelizables deben basarse en las normas internacionales acordadas en enero de 2019 por el Comité de Supervisión Bancaria de Basilea (marco de Basilea) y tener en cuenta la importancia relativa de los requisitos de fondos propios frente a los factores de riesgo no modelizables. Por tanto, conviene establecer metodologías específicas y detalladas para determinar los supuestos extremos de perturbación futura en relación con los factores de riesgo no modelizables.

(2)

La calidad de los datos y el número de observaciones disponibles para determinar las perturbaciones futuras relativas a los factores de riesgo no modelizables pueden variar significativamente entre dichos factores. Así pues, es necesario garantizar que los supuestos extremos de perturbación futura cubran una amplia gama de casos. Por este motivo, es preciso prever conjuntos alternativos de métodos que las entidades puedan utilizar dependiendo de la calidad y el número de observaciones disponibles para cada factor de riesgo no modelizable. Además, las entidades deben reflejar en sus cálculos el hecho de que la disponibilidad de un menor número de datos genera una mayor incertidumbre de las estimaciones o los valores utilizados para determinar los supuestos extremos de perturbación futura, y mostrarse, por tanto, más prudentes.

(3)

Atendiendo a su precisión, uno de los métodos para determinar el supuesto extremo de perturbación futura respecto de un factor de riesgo no modelizable debería consistir en calcular directamente la medida de la pérdida esperada condicional de las pérdidas que se producirían al aplicar una perturbación a ese factor de riesgo no modelizable utilizando los niveles históricamente observados durante el período de tensión pertinente. Sin embargo, ese método solo proporcionaría resultados fiables si la entidad dispusiera de una cantidad significativa de datos con respecto a ese período de tensión, y requeriría numerosos cálculos de pérdidas por factor de riesgo, lo que supondría una enorme labor de cómputo. Por lo tanto, es necesario prever un método alternativo que requiera un número significativamente menor de cálculos de pérdidas y siga un enfoque por etapas. Con arreglo a ese método alternativo, las entidades deben calcular primero una medida de la pérdida esperada condicional en relación con los rendimientos observados para un factor de riesgo no modelizable y, seguidamente, calcular la pérdida que corresponda a la variación del factor de riesgo identificada por dicha medida de la pérdida esperada condicional. Este enfoque por etapas también debe contemplar el caso concreto en que el número de observaciones relativas a un factor de riesgo no modelizable en el período de tensión considerado sea insuficiente para obtener estimaciones precisas y prudentes. Dado que esta situación se producirá presumiblemente en contadas ocasiones, conviene abordar tales casos aprovechando las metodologías que las entidades hayan implementado con respecto a otros factores de riesgo no modelizables para los que dispongan de más observaciones o, cuando sea posible, valiéndose del método estándar alternativo.

(4)

El marco de Basilea exige que los requisitos de fondos propios por riesgo de mercado en relación con los factores de riesgo no modelizables se calibren en función de un período de tensión idéntico para todos los factores de riesgo no modelizables que pertenezcan a la misma categoría general de factores de riesgo. Para determinar los supuestos extremos de perturbación futura sobre la base de los datos observados durante el período así identificado, las entidades deben recopilar datos sobre los factores de riesgo no modelizables en ese período de tensión identificado.

(5)

Con vistas a armonizar el cálculo de las medidas del riesgo en un supuesto de tensión entre todas las entidades de la Unión, es necesario especificar la forma en que estas deben determinar el período de tensión. Dichas especificaciones deben ser proporcionadas a su finalidad y no requerir una labor de cómputo excesiva ni la aplicación de métodos específicos de fijación de precios. La crisis financiera mundial de 2007-2008 fue uno de los momentos de mayor tensión del sistema financiero. Por tanto, el período de tensión que habrá de determinarse debe comenzar al menos a partir del 1 de enero de 2007. A fin de garantizar que el período de tensión siga siendo pertinente para su cartera de negociación, las entidades deben revisar periódicamente dicho período. No obstante, con vistas a limitar la carga administrativa de las entidades, únicamente debe exigirse que la frecuencia de dicha revisión se ajuste al menos a la misma frecuencia (trimestral) que la correspondiente presentación de información con fines de supervisión.

(6)

El marco de Basilea exige que las entidades determinen supuestos extremos de perturbación futura utilizando los métodos de fijación de precios de su modelo de medición del riesgo, ya que estos métodos se emplean en el contexto de las pruebas retrospectivas y la prueba de atribución de pérdidas y ganancias. Puede haber supuestos de perturbación futura en los que esos métodos de fijación de precios no puedan determinar la correspondiente pérdida de algunos instrumentos financieros o materias primas. En tal caso, las entidades deben actuar de manera prudencialmente correcta y centrarse únicamente en aquellos instrumentos que se vean afectados por el fallo en la fijación de precios. Las metodologías implementadas por la entidad para abordar estos casos no deben afectar en modo alguno a los resultados de las pruebas retrospectivas ni a los requisitos de atribución de pérdidas y ganancias establecidos en el Reglamento Delegado (UE) 2022/2059 de la Comisión (2).

(7)

El artículo 325 ter duodecies, apartado 3, párrafo segundo, del Reglamento (UE) n.o 575/2013 exige que el nivel de los requisitos de fondos propios por riesgo de mercado de un factor de riesgo no modelizable sea tan elevado como la medida de la pérdida esperada condicional para ese factor de riesgo a que se refiere el artículo 325 ter ter de dicho Reglamento, es decir, una pérdida esperada condicional de pérdidas con un nivel de confianza del 97,5 % durante un período de tensión. Por tanto, los estimadores estadísticos y los parámetros para determinar esa medida de la pérdida esperada condicional deben fijarse de tal manera que se verifique ese nivel de confianza.

(8)

Con arreglo al marco de Basilea, el supuesto extremo reglamentario de perturbación futura debe ser el que da lugar a la máxima pérdida posible por la variación del factor de riesgo no modelizable. Por tanto, debe especificarse lo que las entidades han de considerar la pérdida máxima en los casos en que esta no sea finita.

(9)

En aras de la coherencia con el marco de Basilea, las entidades deben poder determinar la medida del riesgo en un supuesto de tensión para varios factores de riesgo no modelizables cuando estos formen parte de una curva o una superficie y pertenezcan al mismo segmento no modelizable entre los establecidos en el Reglamento Delegado (UE) 2022/2060 de la Comisión (3), y siempre que las entidades hayan evaluado su modelizabilidad de conformidad con el método de segmentación estándar a que se refiere dicho Reglamento Delegado. Por consiguiente, las entidades deben estar autorizadas a calcular una única medida del riesgo en un supuesto de tensión con respecto a varios factores de riesgo no modelizables solamente en las citadas condiciones.

(10)

Para garantizar la adecuación de los requisitos de fondos propios por factores de riesgo no modelizables al perfil de riesgo de las entidades, estas deben reflejar en la agregación de las medidas del riesgo en un supuesto de tensión aquellos riesgos que aún no hayan quedado recogidos al determinar el supuesto extremo de perturbación futura, incluidos los horizontes de liquidez de los factores de riesgo no modelizables. Con vistas a asegurar unas condiciones de competencia equitativas, las medidas del riesgo en un supuesto de tensión deben agregarse aplicando la fórmula de agregación acordada en el marco de Basilea.

(11)

El presente Reglamento se basa en los proyectos de normas técnicas de regulación presentados por la Autoridad Bancaria Europea a la Comisión.

(12)

La Autoridad Bancaria Europea ha llevado a cabo consultas públicas abiertas sobre los proyectos de normas técnicas de regulación en que se basa el presente Reglamento, ha analizado los costes y beneficios potenciales correspondientes y ha recabado el asesoramiento del Grupo de Partes Interesadas del Sector Bancario creado de conformidad con el artículo 37 del Reglamento (UE) n.o 1093/2010 del Parlamento Europeo y del Consejo (4).

HA ADOPTADO EL PRESENTE REGLAMENTO:

CAPÍTULO 1
DESARROLLO Y APLICACIÓN DE LOS SUPUESTOS EXTREMOS DE PERTURBACIÓN FUTURA
Artículo 1

Desarrollo de los supuestos extremos de perturbación futura y aplicación de los supuestos al nivel de los factores de riesgo

Las entidades desarrollarán los supuestos extremos de perturbación futura respecto de los factores de riesgo no modelizables aplicando uno de los métodos siguientes:

a)

el método directo establecido en el artículo 2, siempre que se cumplan todas las condiciones siguientes:

i)

que las entidades tengan criterios para decidir si utilizan el método directo a que se refiere la letra a) o el método por etapas a que se refiere la letra b), y dichos criterios sean coherentes a lo largo del tiempo;

ii)

que, a efectos de la letra a), inciso i), las entidades documenten todos los casos en que cambien de método pasando del método directo a que se refiere la letra a) al método por etapas a que se refiere la letra b), o a la inversa, e indiquen la justificación de tal cambio;

iii)

que, a efectos de seguimiento interno, las entidades determinen el supuesto extremo de perturbación futura de conformidad con el método por etapas a que se refiere la letra b) diariamente durante los veinte días hábiles anteriores a cada fecha de información sobre los requisitos de fondos propios por riesgo de mercado;

iv)

que el número de pérdidas en la serie temporal de pérdidas a que se refiere el artículo 2, apartado 1, letra a), inciso iii), sea igual o superior a 200;

b)

el método por etapas establecido en el artículo 3.

Artículo 2

Método directo — factores de riesgo no modelizables

1.   Con arreglo al método directo, las entidades realizarán las operaciones que a continuación se indican en el siguiente orden:

a)

determinarán una serie temporal de pérdidas del siguiente modo:

i)

determinarán, de conformidad con el artículo 3, la serie temporal de rendimientos de diez días hábiles para el factor de riesgo no modelizable en el período de tensión determinado de conformidad con el artículo 12;

ii)

aplicarán al valor del factor de riesgo no modelizable las perturbaciones que correspondan a los rendimientos de la serie temporal de rendimientos de diez días hábiles determinada de conformidad con el inciso i);

iii)

determinarán la serie temporal de pérdidas calculando las pérdidas que se producirían si el factor de riesgo no modelizable tomara los valores obtenidos de conformidad con el inciso ii);

b)

calcularán la estimación de la pérdida esperada condicional de la cola derecha de conformidad con el artículo 11, apartado 2, para la serie temporal de pérdidas obtenida de conformidad con la letra a).

2.   Al final del proceso establecido en el párrafo primero, la perturbación que dé lugar a una pérdida igual a la estimación a que se refiere el apartado 1, letra b), constituirá el supuesto extremo de perturbación futura respecto del factor de riesgo no modelizable.

Artículo 3

Método por etapas — factores de riesgo no modelizables

1.   Con arreglo al método por etapas, las entidades realizarán las operaciones que a continuación se indican en el siguiente orden:

a)

determinarán, de conformidad con el artículo 7, la serie temporal de rendimientos de diez días hábiles para el factor de riesgo no modelizable en el período de tensión determinado de conformidad con el artículo 12;

b)

determinarán una perturbación calibrada al alza y una perturbación calibrada a la baja a partir de la serie temporal de rendimientos de diez días hábiles a que se refiere la letra a) con arreglo:

i)

al método histórico establecido en el artículo 8, cuando el número de rendimientos en la serie temporal de diez días hábiles a que se refiere la letra a) del presente apartado sea igual o superior a 200;

ii)

al método sigma asimétrico establecido en el artículo 9, cuando el número de rendimientos en la serie temporal de diez días hábiles a que se refiere la letra a) del presente apartado sea inferior a 200 e igual o superior a 12;

iii)

al método alternativo establecido en el artículo 10, cuando el número de rendimientos en la serie temporal de diez días hábiles a que se refiere la letra a) del presente apartado sea inferior a 12;

c)

en relación con cada perturbación incluida en la siguiente parrilla, las entidades calcularán la pérdida que se produce al aplicar esa perturbación al factor de riesgo no modelizable:

 

Imagen: data:image/jpg;base64,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

 

donde:

CSdown es la perturbación calibrada a la baja determinada de conformidad con la letra b);

CSup es la perturbación calibrada al alza determinada de conformidad con la letra b).

2.   La perturbación que dé lugar a la pérdida más elevada, entre las perturbaciones incluidas en la parrilla a que se refiere el apartado 1, letra c), constituirá el supuesto extremo de perturbación futura respecto del factor de riesgo no modelizable.

Artículo 4

Desarrollo y aplicación de los supuestos extremos de perturbación futura al nivel de los segmentos estándar

Cuando las entidades calculen una medida del riesgo en un supuesto de tensión en relación con varios factores de riesgo no modelizables, determinarán el supuesto extremo de perturbación futura para el segmento estándar no modelizable al que pertenezcan dichos factores de riesgo de conformidad con el Reglamento Delegado (UE) 2022/2060 aplicando uno de los métodos siguientes:

a)

el método directo establecido en el artículo 5, siempre que se cumplan todas las condiciones siguientes:

i)

que las entidades tengan criterios definidos para decidir si utilizan el método directo a que se refiere el artículo 5 o el método por etapas a que se refiere el artículo 6, y dichos criterios sean coherentes a lo largo del tiempo;

ii)

que, a efectos de la letra a), inciso i), las entidades documenten todos los casos en que cambien de método pasando del método directo al método por etapas, o a la inversa, e indiquen la justificación de tal cambio;

iii)

que, paralelamente a la utilización del método directo, las entidades determinen con carácter complementario el supuesto extremo de perturbación futura de conformidad con el método por etapas a que se refiere la letra b) diariamente durante los veinte días hábiles anteriores a cada fecha de información sobre los requisitos de fondos propios por riesgo de mercado;

iv)

que el número de pérdidas en la serie temporal de pérdidas a que se refiere el artículo 5, apartado 1, letra a), inciso iv), sea igual o superior a 200;

b)

el método por etapas establecido en el artículo 6.

Artículo 5

Método directo — segmentos estándar no modelizables

1.   Al aplicar el método directo a los factores de riesgo no modelizables pertenecientes a segmentos estándar no modelizables, las entidades realizarán las operaciones que a continuación se indican en el siguiente orden:

a)

determinarán una serie temporal de pérdidas del siguiente modo:

i)

respecto de cada factor de riesgo no modelizable dentro del segmento no modelizable, determinarán, de conformidad con el artículo 7, la serie temporal de rendimientos más próxima a los diez días hábiles en el período de tensión determinado de conformidad con el artículo 12;

ii)

eliminarán de cada serie temporal obtenida de conformidad con el inciso i) los valores correspondientes a las fechas en que no todas esas series temporales tengan un rendimiento;

iii)

respecto de cada factor de riesgo no modelizable dentro del segmento no modelizable, aplicarán al valor del factor de riesgo no modelizable las perturbaciones que correspondan a los rendimientos de la pertinente serie temporal obtenida de conformidad con el inciso ii);

iv)

determinarán la serie temporal de pérdidas calculando, para cada fecha correspondiente a un valor en las series temporales obtenidas de conformidad con el inciso iii), la pérdida que se produciría si los factores de riesgo no modelizables del segmento no modelizable tomaran los valores incluidos en dichas series temporales respecto de esa fecha;

b)

calcularán la estimación de la pérdida esperada condicional de la cola derecha de conformidad con el artículo 11, apartado 2, para la serie temporal de pérdidas obtenida de conformidad con la letra a) del presente apartado.

2.   El supuesto de perturbación que dé lugar a una pérdida igual a la estimación de la pérdida esperada condicional de la cola derecha obtenida de conformidad con el apartado 1, letra b), constituirá el supuesto extremo de perturbación futura respecto del segmento no modelizable.

Artículo 6

Método por etapas – segmentos estándar no modelizables

1.   Al aplicar el método por etapas a los factores de riesgo no modelizables pertenecientes a segmentos estándar no modelizables, las entidades determinarán el supuesto extremo de perturbación futura realizando las operaciones que a continuación se indican en el siguiente orden:

a)

respecto de cada factor de riesgo no modelizable dentro del segmento estándar no modelizable, determinarán, de conformidad con el artículo 7, la serie temporal de rendimientos de diez días hábiles en el período de tensión determinado de conformidad con el artículo 12;

b)

respecto de cada factor de riesgo no modelizable dentro del segmento estándar no modelizable, determinarán una perturbación calibrada al alza y una perturbación calibrada a la baja a partir de la correspondiente serie temporal de rendimientos de diez días hábiles a que se refiere la letra a) con arreglo:

i)

al método histórico establecido en el artículo 8, cuando el número de rendimientos en todas las series temporales de diez días hábiles a que se refiere la letra a) del presente apartado correspondientes a los factores de riesgo no modelizables del segmento no modelizable sea igual o superior a 200;

ii)

al método sigma asimétrico establecido en el artículo 9, cuando no se cumpla la condición de la letra b), inciso i), del presente apartado para utilizar el método histórico y el número de rendimientos en todas las series temporales de diez días hábiles a que se refiere la letra a) del presente apartado correspondientes a los factores de riesgo no modelizables del segmento no modelizable sea igual o superior a 12;

iii)

al método alternativo establecido en el artículo 10, cuando haya al menos un factor de riesgo no modelizable en el segmento no modelizable con respecto al cual el número de rendimientos en la serie temporal de diez días hábiles a que se refiere la letra a) del presente apartado sea inferior a 12;

c)

calcularán los dos elementos siguientes:

i)

la pérdida correspondiente al supuesto en que se aplique a cada factor de riesgo del segmento no modelizable la correspondiente perturbación calibrada al alza determinada de conformidad con la letra b) multiplicada por un parámetro β;

ii)

la pérdida correspondiente al supuesto en que se aplique a cada factor de riesgo del segmento no modelizable la correspondiente perturbación calibrada a la baja determinada de conformidad con la letra b) multiplicada por un parámetro β.

A efectos de la letra c), las entidades multiplicarán las perturbaciones calibradas al alza y a la baja por el parámetro β en dos casos: β = 1 y β = ⅘.

2.   El supuesto de perturbación que dé lugar a la pérdida más elevada entre las calculadas de conformidad con el apartado 1, letra c), constituirá el supuesto extremo de perturbación futura respecto del segmento estándar no modelizable.

Artículo 7

Determinación de la serie temporal de rendimientos de diez días hábiles

1.   Las entidades determinarán la serie temporal de rendimientos de diez días hábiles en el período de tensión en relación con un factor de riesgo no modelizable dado realizando las operaciones que a continuación se indican en el siguiente orden:

a)

determinarán la serie temporal de observaciones correspondiente al factor de riesgo no modelizable en el período de tensión e incluirán en dicha serie temporal solo una observación por día hábil que representará los datos de mercado reales;

b)

ampliarán la serie temporal a que se refiere la letra a) incluyendo las observaciones disponibles en el período de veinte días hábiles posterior al período de tensión; cuando la fecha de referencia para el cálculo de la medida del riesgo en un supuesto de tensión se sitúe menos de veinte días hábiles después del final del período de tensión, las entidades incluirán las observaciones disponibles desde el final del período de tensión hasta la fecha de referencia;

c)

en relación con cada fecha D t para la que exista una observación en la serie temporal resultante de la letra a), excluida la última observación, las entidades determinarán, entre las fechas para las que exista una observación en la serie temporal ampliada a que se refiere la letra b), la fecha

 

Imagen: data:image/jpg;base64,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

 

posterior a la fecha D t que minimice el valor siguiente:

 

Imagen: data:image/jpg;base64,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

 

donde:

Dt es la fecha para la que existe una observación en la serie temporal a que se refiere la letra a), excluida la última observación;

 

Imagen: data:image/jpg;base64,/9j/4AAQSkZJRgABAQABLAEsAAD/4gogSUNDX1BST0ZJTEUAAQEAAAoQAAAAAAIQAABtbnRyUkdCIFhZWiAAAAAAAAAAAAAAAABhY3NwQVBQTAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA9tYAAQAAAADTLQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAApkZXNjAAAA/AAAAHxjcHJ0AAABeAAAACh3dHB0AAABoAAAABRia3B0AAABtAAAABRyWFlaAAAByAAAABRnWFlaAAAB3AAAABRiWFlaAAAB8AAAABRyVFJDAAACBAAACAxnVFJDAAACBAAACAxiVFJDAAACBAAACAxkZXNjAAAAAAAAACJBcnRpZmV4IFNvZnR3YXJlIHNSR0IgSUNDIFByb2ZpbGUAAAAAAAAAAAAAACJBcnRpZmV4IFNvZnR3YXJlIHNSR0IgSUNDIFByb2ZpbGUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAdGV4dAAAAABDb3B5cmlnaHQgQXJ0aWZleCBTb2Z0d2FyZSAyMDExAFhZWiAAAAAAAADzUQABAAAAARbMWFlaIAAAAAAAAAAAAAAAAAAAAABYWVogAAAAAAAAb6IAADj1AAADkFhZWiAAAAAAAABimQAAt4UAABjaWFlaIAAAAAAAACSgAAAPhAAAts9jdXJ2AAAAAAAABAAAAAAFAAoADwAUABkAHgAjACgALQAyADcAOwBAAEUASgBPAFQAWQBeAGMAaABtAHIAdwB8AIEAhgCLAJAAlQCaAJ8ApACpAK4AsgC3ALwAwQDGAMsA0ADVANsA4ADlAOsA8AD2APsBAQEHAQ0BEwEZAR8BJQErATIBOAE+AUUBTAFSAVkBYAFnAW4BdQF8AYMBiwGSAZoBoQGpAbEBuQHBAckB0QHZAeEB6QHyAfoCAwIMAhQCHQImAi8COAJBAksCVAJdAmcCcQJ6AoQCjgKYAqICrAK2AsECywLVAuAC6wL1AwADCwMWAyEDLQM4A0MDTwNaA2YDcgN+A4oDlgOiA64DugPHA9MD4APsA/kEBgQTBCAELQQ7BEgEVQRjBHEEfgSMBJoEqAS2BMQE0wThBPAE/gUNBRwFKwU6BUkFWAVnBXcFhgWWBaYFtQXFBdUF5QX2BgYGFgYnBjcGSAZZBmoGewaMBp0GrwbABtEG4wb1BwcHGQcrBz0HTwdhB3QHhgeZB6wHvwfSB+UH+AgLCB8IMghGCFoIbgiCCJYIqgi+CNII5wj7CRAJJQk6CU8JZAl5CY8JpAm6Cc8J5Qn7ChEKJwo9ClQKagqBCpgKrgrFCtwK8wsLCyILOQtRC2kLgAuYC7ALyAvhC/kMEgwqDEMMXAx1DI4MpwzADNkM8w0NDSYNQA1aDXQNjg2pDcMN3g34DhMOLg5JDmQOfw6bDrYO0g7uDwkPJQ9BD14Peg+WD7MPzw/sEAkQJhBDEGEQfhCbELkQ1xD1ERMRMRFPEW0RjBGqEckR6BIHEiYSRRJkEoQSoxLDEuMTAxMjE0MTYxODE6QTxRPlFAYUJxRJFGoUixStFM4U8BUSFTQVVhV4FZsVvRXgFgMWJhZJFmwWjxayFtYW+hcdF0EXZReJF64X0hf3GBsYQBhlGIoYrxjVGPoZIBlFGWsZkRm3Gd0aBBoqGlEadxqeGsUa7BsUGzsbYxuKG7Ib2hwCHCocUhx7HKMczBz1HR4dRx1wHZkdwx3sHhYeQB5qHpQevh7pHxMfPh9pH5Qfvx/qIBUgQSBsIJggxCDwIRwhSCF1IaEhziH7IiciVSKCIq8i3SMKIzgjZiOUI8Ij8CQfJE0kfCSrJNolCSU4JWgllyXHJfcmJyZXJocmtyboJxgnSSd6J6sn3CgNKD8ocSiiKNQpBik4KWspnSnQKgIqNSpoKpsqzysCKzYraSudK9EsBSw5LG4soizXLQwtQS12Last4S4WLkwugi63Lu4vJC9aL5Evxy/+MDUwbDCkMNsxEjFKMYIxujHyMioyYzKbMtQzDTNGM38zuDPxNCs0ZTSeNNg1EzVNNYc1wjX9Njc2cjauNuk3JDdgN5w31zgUOFA4jDjIOQU5Qjl/Obw5+To2OnQ6sjrvOy07azuqO+g8JzxlPKQ84z0iPWE9oT3gPiA+YD6gPuA/IT9hP6I/4kAjQGRApkDnQSlBakGsQe5CMEJyQrVC90M6Q31DwEQDREdEikTORRJFVUWaRd5GIkZnRqtG8Ec1R3tHwEgFSEtIkUjXSR1JY0mpSfBKN0p9SsRLDEtTS5pL4kwqTHJMuk0CTUpNk03cTiVObk63TwBPSU+TT91QJ1BxULtRBlFQUZtR5lIxUnxSx1MTU19TqlP2VEJUj1TbVShVdVXCVg9WXFapVvdXRFeSV+BYL1h9WMtZGllpWbhaB1pWWqZa9VtFW5Vb5Vw1XIZc1l0nXXhdyV4aXmxevV8PX2Ffs2AFYFdgqmD8YU9homH1YklinGLwY0Njl2PrZEBklGTpZT1lkmXnZj1mkmboZz1nk2fpaD9olmjsaUNpmmnxakhqn2r3a09rp2v/bFdsr20IbWBtuW4SbmtuxG8eb3hv0XArcIZw4HE6cZVx8HJLcqZzAXNdc7h0FHRwdMx1KHWFdeF2Pnabdvh3VnezeBF4bnjMeSp5iXnnekZ6pXsEe2N7wnwhfIF84X1BfaF+AX5ifsJ/I3+Ef+WAR4CogQqBa4HNgjCCkoL0g1eDuoQdhICE44VHhauGDoZyhteHO4efiASIaYjOiTOJmYn+imSKyoswi5aL/IxjjMqNMY2Yjf+OZo7OjzaPnpAGkG6Q1pE/kaiSEZJ6kuOTTZO2lCCUipT0lV+VyZY0lp+XCpd1l+CYTJi4mSSZkJn8mmia1ZtCm6+cHJyJnPedZJ3SnkCerp8dn4uf+qBpoNihR6G2oiailqMGo3aj5qRWpMelOKWpphqmi6b9p26n4KhSqMSpN6mpqhyqj6sCq3Wr6axcrNCtRK24ri2uoa8Wr4uwALB1sOqxYLHWskuywrM4s660JbSctRO1irYBtnm28Ldot+C4WbjRuUq5wro7urW7LrunvCG8m70VvY++Cr6Evv+/er/1wHDA7MFnwePCX8Lbw1jD1MRRxM7FS8XIxkbGw8dBx7/IPci8yTrJuco4yrfLNsu2zDXMtc01zbXONs62zzfPuNA50LrRPNG+0j/SwdNE08bUSdTL1U7V0dZV1tjXXNfg2GTY6Nls2fHadtr724DcBdyK3RDdlt4c3qLfKd+v4DbgveFE4cziU+Lb42Pj6+Rz5PzlhOYN5pbnH+ep6DLovOlG6dDqW+rl63Dr++yG7RHtnO4o7rTvQO/M8Fjw5fFy8f/yjPMZ86f0NPTC9VD13vZt9vv3ivgZ+Kj5OPnH+lf65/t3/Af8mP0p/br+S/7c/23////bAEMAAwICAgICAwICAgMDAwMEBgQEBAQECAYGBQYJCAoKCQgJCQoMDwwKCw4LCQkNEQ0ODxAQERAKDBITEhATDxAQEP/AAAsIACMAKQEBEQD/xAAcAAABBQADAAAAAAAAAAAAAAAAAQUGBwgCAwn/xAAwEAABAwMDAwEECwAAAAAAAAABAgMEBQYHABESCBMhMQkiQVEUFiMzN1JhZIGRsf/aAAgBAQAAPwD05vK76HYVtzbtuRc1NNp6UqfVCp0ic8ApYSCliOhbq/KhvxSdhuTsASKXofXp0vXPSJlwW1e1eq9Lp5WmXOp9lV2THjlCQtYccbhlKCEkKIJGwIPpq2se5Ox9ligC6Mb3jSrjpZcUyqTT5KXUtuJ9W1geULHjdKgD5HjUo0aNcV+n8j/dYP8AZDkqxHlAFSvxLqPx/axdd18BnAftM7Cm2e65T6NnCjSolyUuKjizKqMcOFuYtO4RzKu1uoAq+9PkunW6wQU8vhtvpjt6+bRuyp1yj23cMKozbaminVZmO5yVDklCV9pz5K4qB2/X56fdMl6XG/aVtTLhj2zWrgcidspptGYbemP8nEp+zQ4tCTty5HdQ91JPn0OE+g85Z6ZrDvK2sg9NmU35lxXhLr8U0ymwn0JjOssoSFky07L3bVukAgDbyd/FnWHifJ2TOptXWBme1ZloUu06A5SrLtQykzKihC0u9+VLbj82w6tLi+LSFKVupAJ3bHKbYC6roObbqvW2o9q3PFNFueZR6U+/adSiMBiPDjuLTNfdQWmJHeW+ntLU2vj2t0Aq8zLpxxDJw5jZujV2TFm3TW50q4rpnxge3MrEx0uyVpKveKElQbQVeeDaN/O+rR0hAPgjfScEflH9aUj3SB8tZtwnjDN2L8r3vSXqdR/qXdF/1i/Xa01UApyQxNipZap30Yo5odbeQh1bm/ApQAlRJKdaT0aNGjRo0a//2Q== es una fecha posterior a Dt para la que existe una observación en la serie temporal ampliada a que se refiere la letra b);

 

la diferencia

Imagen: data:image/jpg;base64,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 se expresa en días hábiles;

 

d)

en relación con cada fecha D t para la que exista una observación en la serie temporal resultante de la letra a), excluida la última observación, las entidades determinarán el correspondiente rendimiento de diez días hábiles determinando el rendimiento correspondiente al factor de riesgo no modelizable en el período comprendido entre la fecha D t de la observación y la fecha

 

Imagen: data:image/jpg;base64,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

 

que minimiza el valor v de conformidad con la letra c), y reajustándolo seguidamente para obtener un rendimiento a lo largo de un período de diez días hábiles mediante la multiplicación del rendimiento por

 

Imagen: data:image/jpg;base64,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

 

.
A efectos de la letra c), cuando haya más de una fecha que minimice ese valor, la fecha

 

Imagen: data:image/jpg;base64,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

 

será la última en el tiempo de entre las fechas que minimicen el valor.

2.   La serie temporal a que se refiere el apartado 1, letra a), incluirá, como mínimo, las observaciones utilizadas para calibrar los supuestos de perturbaciones futuras a que se refiere el artículo 325 ter quater del Reglamento (UE) n.o 575/2013, cuando el factor de riesgo en cuestión se hubiera considerado previamente modelizable de conformidad con el artículo 325 ter sexies de dicho Reglamento.

Artículo 8

Perturbaciones calibradas a la baja y al alza con el método histórico

1.   Con arreglo al método histórico, las entidades determinarán la perturbación calibrada a la baja a partir de una serie temporal de rendimientos de diez días hábiles correspondiente a un factor de riesgo no modelizable aplicando la siguiente fórmula:

 

Imagen: data:image/jpg;base64,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

 

donde:

Ret representa la serie temporal de rendimientos de diez días hábiles del factor de riesgo no modelizable;

 

Imagen: data:image/jpg;base64,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 es la estimación de la pérdida esperada condicional de la cola izquierda para la serie temporal Ret calculada de conformidad con el artículo 11, apartado 1;

 

N es el número de rendimientos en la serie temporal Ret.

2.   Con arreglo al método histórico, las entidades determinarán la perturbación calibrada al alza a partir de una serie temporal de rendimientos de diez días hábiles correspondiente a un factor de riesgo no modelizable aplicando la siguiente fórmula:

 

Imagen: data:image/jpg;base64,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

 

donde:

Ret representa la serie temporal de rendimientos de diez días hábiles del factor de riesgo no modelizable;

 

Imagen: data:image/jpg;base64,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 es la estimación de la pérdida esperada condicional de la cola derecha para la serie temporal Ret calculada de conformidad con el artículo 11, apartado 2;

 

N es el número de rendimientos en la serie temporal Ret.

Artículo 9

Perturbaciones calibradas a la baja y al alza con el método sigma asimétrico

Con arreglo al método sigma asimétrico, las entidades determinarán las perturbaciones calibradas a la baja y al alza a partir de una serie temporal de rendimientos de diez días hábiles correspondiente a un factor de riesgo no modelizable realizando las operaciones que a continuación se indican en el siguiente orden:

a)

determinarán la mediana de los rendimientos de la serie temporal y dividirán los rendimientos de diez días hábiles incluidos en dicha serie temporal en los dos subconjuntos siguientes:

i)

el subconjunto de rendimientos de diez días hábiles cuyo valor es igual o inferior a la mediana;

ii)

el subconjunto de rendimientos de diez días hábiles cuyo valor es superior a la mediana;

b)

en relación con cada uno de los subconjuntos a que se refiere la letra a), calcularán la media de los rendimientos de diez días hábiles del subconjunto;

c)

determinarán la perturbación calibrada a la baja con arreglo a la siguiente fórmula:

perturbación calibrada a la baja

 

Imagen: data:image/jpg;base64,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

 

donde:

Ret representa la serie temporal de rendimientos de diez días hábiles del factor de riesgo no modelizable;

Reti es el i-ésimo rendimiento de la serie temporal de diez días hábiles Ret;

m es la mediana de los rendimientos de la serie temporal de diez días hábiles Ret;

 

Imagen: data:image/jpg;base64,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 representa la media de los rendimientos de diez días hábiles calculada de conformidad con la letra b) en relación con el subconjunto determinado de conformidad con la letra a), inciso i);

 

Ndown es el número de rendimientos de diez días hábiles incluidos en el subconjunto determinado de conformidad con la letra a), inciso i);

N es el número de rendimientos de la serie temporal de diez días hábiles Ret;

 

Imagen: data:image/jpg;base64,/9j/4AAQSkZJRgABAQABLAEsAAD/4gogSUNDX1BST0ZJTEUAAQEAAAoQAAAAAAIQAABtbnRyUkdCIFhZWiAAAAAAAAAAAAAAAABhY3NwQVBQTAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA9tYAAQAAAADTLQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAApkZXNjAAAA/AAAAHxjcHJ0AAABeAAAACh3dHB0AAABoAAAABRia3B0AAABtAAAABRyWFlaAAAByAAAABRnWFlaAAAB3AAAABRiWFlaAAAB8AAAABRyVFJDAAACBAAACAxnVFJDAAACBAAACAxiVFJDAAACBAAACAxkZXNjAAAAAAAAACJBcnRpZmV4IFNvZnR3YXJlIHNSR0IgSUNDIFByb2ZpbGUAAAAAAAAAAAAAACJBcnRpZmV4IFNvZnR3YXJlIHNSR0IgSUNDIFByb2ZpbGUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAdGV4dAAAAABDb3B5cmlnaHQgQXJ0aWZleCBTb2Z0d2FyZSAyMDExAFhZWiAAAAAAAADzUQABAAAAARbMWFlaIAAAAAAAAAAAAAAAAAAAAABYWVogAAAAAAAAb6IAADj1AAADkFhZWiAAAAAAAABimQAAt4UAABjaWFlaIAAAAAAAACSgAAAPhAAAts9jdXJ2AAAAAAAABAAAAAAFAAoADwAUABkAHgAjACgALQAyADcAOwBAAEUASgBPAFQAWQBeAGMAaABtAHIAdwB8AIEAhgCLAJAAlQCaAJ8ApACpAK4AsgC3ALwAwQDGAMsA0ADVANsA4ADlAOsA8AD2APsBAQEHAQ0BEwEZAR8BJQErATIBOAE+AUUBTAFSAVkBYAFnAW4BdQF8AYMBiwGSAZoBoQGpAbEBuQHBAckB0QHZAeEB6QHyAfoCAwIMAhQCHQImAi8COAJBAksCVAJdAmcCcQJ6AoQCjgKYAqICrAK2AsECywLVAuAC6wL1AwADCwMWAyEDLQM4A0MDTwNaA2YDcgN+A4oDlgOiA64DugPHA9MD4APsA/kEBgQTBCAELQQ7BEgEVQRjBHEEfgSMBJoEqAS2BMQE0wThBPAE/gUNBRwFKwU6BUkFWAVnBXcFhgWWBaYFtQXFBdUF5QX2BgYGFgYnBjcGSAZZBmoGewaMBp0GrwbABtEG4wb1BwcHGQcrBz0HTwdhB3QHhgeZB6wHvwfSB+UH+AgLCB8IMghGCFoIbgiCCJYIqgi+CNII5wj7CRAJJQk6CU8JZAl5CY8JpAm6Cc8J5Qn7ChEKJwo9ClQKagqBCpgKrgrFCtwK8wsLCyILOQtRC2kLgAuYC7ALyAvhC/kMEgwqDEMMXAx1DI4MpwzADNkM8w0NDSYNQA1aDXQNjg2pDcMN3g34DhMOLg5JDmQOfw6bDrYO0g7uDwkPJQ9BD14Peg+WD7MPzw/sEAkQJhBDEGEQfhCbELkQ1xD1ERMRMRFPEW0RjBGqEckR6BIHEiYSRRJkEoQSoxLDEuMTAxMjE0MTYxODE6QTxRPlFAYUJxRJFGoUixStFM4U8BUSFTQVVhV4FZsVvRXgFgMWJhZJFmwWjxayFtYW+hcdF0EXZReJF64X0hf3GBsYQBhlGIoYrxjVGPoZIBlFGWsZkRm3Gd0aBBoqGlEadxqeGsUa7BsUGzsbYxuKG7Ib2hwCHCocUhx7HKMczBz1HR4dRx1wHZkdwx3sHhYeQB5qHpQevh7pHxMfPh9pH5Qfvx/qIBUgQSBsIJggxCDwIRwhSCF1IaEhziH7IiciVSKCIq8i3SMKIzgjZiOUI8Ij8CQfJE0kfCSrJNolCSU4JWgllyXHJfcmJyZXJocmtyboJxgnSSd6J6sn3CgNKD8ocSiiKNQpBik4KWspnSnQKgIqNSpoKpsqzysCKzYraSudK9EsBSw5LG4soizXLQwtQS12Last4S4WLkwugi63Lu4vJC9aL5Evxy/+MDUwbDCkMNsxEjFKMYIxujHyMioyYzKbMtQzDTNGM38zuDPxNCs0ZTSeNNg1EzVNNYc1wjX9Njc2cjauNuk3JDdgN5w31zgUOFA4jDjIOQU5Qjl/Obw5+To2OnQ6sjrvOy07azuqO+g8JzxlPKQ84z0iPWE9oT3gPiA+YD6gPuA/IT9hP6I/4kAjQGRApkDnQSlBakGsQe5CMEJyQrVC90M6Q31DwEQDREdEikTORRJFVUWaRd5GIkZnRqtG8Ec1R3tHwEgFSEtIkUjXSR1JY0mpSfBKN0p9SsRLDEtTS5pL4kwqTHJMuk0CTUpNk03cTiVObk63TwBPSU+TT91QJ1BxULtRBlFQUZtR5lIxUnxSx1MTU19TqlP2VEJUj1TbVShVdVXCVg9WXFapVvdXRFeSV+BYL1h9WMtZGllpWbhaB1pWWqZa9VtFW5Vb5Vw1XIZc1l0nXXhdyV4aXmxevV8PX2Ffs2AFYFdgqmD8YU9homH1YklinGLwY0Njl2PrZEBklGTpZT1lkmXnZj1mkmboZz1nk2fpaD9olmjsaUNpmmnxakhqn2r3a09rp2v/bFdsr20IbWBtuW4SbmtuxG8eb3hv0XArcIZw4HE6cZVx8HJLcqZzAXNdc7h0FHRwdMx1KHWFdeF2Pnabdvh3VnezeBF4bnjMeSp5iXnnekZ6pXsEe2N7wnwhfIF84X1BfaF+AX5ifsJ/I3+Ef+WAR4CogQqBa4HNgjCCkoL0g1eDuoQdhICE44VHhauGDoZyhteHO4efiASIaYjOiTOJmYn+imSKyoswi5aL/IxjjMqNMY2Yjf+OZo7OjzaPnpAGkG6Q1pE/kaiSEZJ6kuOTTZO2lCCUipT0lV+VyZY0lp+XCpd1l+CYTJi4mSSZkJn8mmia1ZtCm6+cHJyJnPedZJ3SnkCerp8dn4uf+qBpoNihR6G2oiailqMGo3aj5qRWpMelOKWpphqmi6b9p26n4KhSqMSpN6mpqhyqj6sCq3Wr6axcrNCtRK24ri2uoa8Wr4uwALB1sOqxYLHWskuywrM4s660JbSctRO1irYBtnm28Ldot+C4WbjRuUq5wro7urW7LrunvCG8m70VvY++Cr6Evv+/er/1wHDA7MFnwePCX8Lbw1jD1MRRxM7FS8XIxkbGw8dBx7/IPci8yTrJuco4yrfLNsu2zDXMtc01zbXONs62zzfPuNA50LrRPNG+0j/SwdNE08bUSdTL1U7V0dZV1tjXXNfg2GTY6Nls2fHadtr724DcBdyK3RDdlt4c3qLfKd+v4DbgveFE4cziU+Lb42Pj6+Rz5PzlhOYN5pbnH+ep6DLovOlG6dDqW+rl63Dr++yG7RHtnO4o7rTvQO/M8Fjw5fFy8f/yjPMZ86f0NPTC9VD13vZt9vv3ivgZ+Kj5OPnH+lf65/t3/Af8mP0p/br+S/7c/23////bAEMAAwICAgICAwICAgMDAwMEBgQEBAQECAYGBQYJCAoKCQgJCQoMDwwKCw4LCQkNEQ0ODxAQERAKDBITEhATDxAQEP/AAAsIACEAXQEBEQD/xAAdAAACAQUBAQAAAAAAAAAAAAAABwYBAwUICQQC/8QAMRAAAQMDBAECBAMJAAAAAAAAAgEDBAUGBwAIERIhEyIUJDFBGFFYFRcjQkOWl7PT/9oACAEBAAA/AOqekpcu77DdDuqdZVFkXFeVZo5IlZj2jb0ytDShVCVSkuRgJttUQD9nZXPbwgKvjWfx1uOw/lq6HrSx1drVbnRqQ3WZKMNGKRWjfNhGn0NENiQhtmhMOCLg8e4U0zNGjRo0atSpUaDGdmzZDbEdgCddddNBBsBTkiIl8IiIiqqr4RNLuzdyOBsg3Stk2Vlu16xXerhtwItRAnnhDnsTQ/1RThV5DsnCc/Tzpk6143/ZXurDG0++r4sqUUSshHj06LLA1ByKsuQ3HJ5sk8o4AuEQr9iRF+2pDs+xnbGK9t9g25bEJppt+hQ6jLeEOpypchkXnnj8qqkRmv34ROEThERNeIcU2hiHPl57l6jWrZte3LhtmDTq2/LeCGP7QalmqSnnCQW07g402pEXZSEU4+6yQt0u2QS6luLxghfkt3U9F/26yt7ZyxFjui0u4bvyFRIECuNo9S3fiUd+OaURL1GBb7E6HUwVTFFFEMVVfKc5SxMmY+yhBm1THV50e5YNOl/ASZVKlhJZbkek26rfqAqipIDraqiKvHbhfPKJ4Ms5Sg4jtlm56haN3XG29MCGkS2KI9VJYqQmXcmWvcjadFRT+iKQp900oPxyWx+n7cB/jWfqc4i3G0fL9xSbcp+MMn225FhFNWVdFoyaVFMRMA9MHXfaTi+oioH1VBJf5V1I814oo+ccXXBiqv1usUmnXFGSJKlUh8WpIt9xJREjEh6l16kiiqEJEn31pfm6PDvPdFtowRTwmW4OMagFVC4rwjLEerzUL4UEi09zx8Q476Bd0RBRS6Fx1QUPoOn01Ac84foee8RXRiW4JCxotxwCjDKFtHCivIqEy+grx2UHBAuOU54VOU550jcC5ayhg+x4GF9xWKb8lVm0Y6U6Bc1sW7Lr1MrkFrgI7qHDbNxl300ESbdAV9qFzySikzx/RLxyBd13Z2v+1Jls06p281btvW1VBFZYwWXXn3Jc5pFIG3nXDHoyiqrbbad17GohqZsEbylWsBYMtL91dCkY2rFduCFcdYF1udJnQyaqpIzJjFG+WY+IFsfV9ZVIhZHwjijprBZuQ7cuOzskbOLnte+mLbsNizpdv3W4kWTLo0eZLSFJiy2wHr3cYdaQuBbcFlsy7+CFj7KKxbc2BkyC1jyo4+vMbzdn3nasqQ2+zAqj8SP/ABYjgCKFFfBsXhVefcbnCqPVVcWVbTvm87XSjY+yhNsKpLJbdOqw6ZGnOqyKF2aRuSignZVFVLjlEHhPrpP/AIeN0P67Lu/suh/8tTfEeK8x2NcUmq5D3J13IVOehFHapk636dBbZeUwJH0cjNiakgiY9VXrw4qqnKJxY3ZxM/SsI1lzbTWwpt8RHGJMb5Vh9yQwBp6zLSPoraOKHKj2ReevVOFJCTV3cZS8lbtm8I48s2wL4Gs21cEG4LouW4rRl29T4noMoLy/MCik4bikQtMK4icInZU4LXQMU4Tz+arquqcaxlzUFu5qDNoDtSqNPbnNKycinSVjyGxX6q24PkFVOU5TynPjhfOk/b+0DHVpY5ZxJad139RLRj+sjVNp10SI6CLpmbo+qHDvUicNVTvwvZdfLez7HlFl0SpY+uy97GnW7bkW1KfIoNZQelPYeddEHGpDbrUglN9xVJ4DVFVFHqSc6YmLsV29iiiTKVRZtUqcuqz3apVqvVpCSJ9TmuIIk++4giKl0BsBEREABsBEREUTUy0aNU0caro0aNGjRo0aNGjRr//Z ;

 

d)

determinarán la perturbación calibrada al alza con arreglo a la siguiente fórmula:

perturbación calibrada al alza

 

Imagen: data:image/jpg;base64,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

 

donde:

Ret representa la serie temporal de rendimientos de diez días hábiles del factor de riesgo no modelizable;

Reti es el i-ésimo rendimiento de la serie temporal de diez días hábiles Ret;

m es la mediana de los rendimientos de la serie temporal de diez días hábiles Ret;

 

Imagen: data:image/jpg;base64,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 representa la media de los rendimientos de diez días hábiles calculada de conformidad con la letra b) en relación con el subconjunto determinado de conformidad con la letra a), inciso ii);

 

Nup es el número de rendimientos incluidos en el subconjunto determinado de conformidad con la letra a), inciso ii);

N es el número de rendimientos de la serie temporal de diez días hábiles Ret;

 

Imagen: data:image/jpg;base64,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 .

 

Artículo 10

Perturbaciones calibradas a la baja y al alza con el método alternativo

1.   Con arreglo al método alternativo, las entidades determinarán las perturbaciones calibradas a la baja y al alza a partir de una serie temporal de rendimientos de diez días hábiles correspondiente a un factor de riesgo no modelizable aplicando uno de los métodos establecidos en el presente artículo.

2.   Cuando el factor de riesgo no modelizable sea uno de los factores de riesgo definidos en la parte tercera, título IV, capítulo 1 bis, sección 3, subsección 1, del Reglamento (UE) n.o 575/2013, las entidades determinarán las perturbaciones calibradas a la baja y al alza realizando las operaciones que a continuación se indican en el siguiente orden:

a)

determinarán la ponderación de riesgo asignada a dicho factor de riesgo de conformidad con la parte tercera, título IV, capítulo 1 bis, del Reglamento (UE) n.o 575/2013;

b)

multiplicarán dicha ponderación de riesgo por

 

Imagen: data:image/jpg;base64,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

 

donde:

LH es el horizonte de liquidez del factor de riesgo no modelizable a que se refiere el artículo 325 ter quinquies del Reglamento (UE) n.o 575/2013;

c)

las perturbaciones calibradas a la baja y al alza serán el resultado de la letra b).

3.   Cuando el factor de riesgo no modelizable sea un punto de una curva o una superficie y difiera de los demás factores de riesgo definidos en la parte tercera, título IV, capítulo 1 bis, sección 3, subsección 1, del Reglamento (UE) n.o 575/2013 únicamente en lo que respecta a la dimensión del vencimiento, las entidades determinarán las perturbaciones calibradas a la baja y al alza realizando las operaciones que a continuación se indican en el siguiente orden:

a)

entre aquellos factores de riesgo definidos en la parte tercera, título IV, capítulo 1 bis, sección 3, subsección 1, del Reglamento (UE) n.o 575/2013 que difieran del factor de riesgo no modelizable únicamente en lo que respecta a la dimensión del vencimiento, identificarán el factor de riesgo que esté más próximo al factor de riesgo no modelizable en lo que respecta a esa dimensión;

b)

determinarán la ponderación de riesgo asignada, de conformidad con la parte tercera, título IV, capítulo 1 bis, del Reglamento (UE) n.o 575/2013, al factor de riesgo identificado con arreglo a la letra a);

c)

multiplicarán dicha ponderación de riesgo por

 

Imagen: data:image/jpg;base64,/9j/4AAQSkZJRgABAQABLAEsAAD/4gogSUNDX1BST0ZJTEUAAQEAAAoQAAAAAAIQAABtbnRyUkdCIFhZWiAAAAAAAAAAAAAAAABhY3NwQVBQTAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA9tYAAQAAAADTLQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAApkZXNjAAAA/AAAAHxjcHJ0AAABeAAAACh3dHB0AAABoAAAABRia3B0AAABtAAAABRyWFlaAAAByAAAABRnWFlaAAAB3AAAABRiWFlaAAAB8AAAABRyVFJDAAACBAAACAxnVFJDAAACBAAACAxiVFJDAAACBAAACAxkZXNjAAAAAAAAACJBcnRpZmV4IFNvZnR3YXJlIHNSR0IgSUNDIFByb2ZpbGUAAAAAAAAAAAAAACJBcnRpZmV4IFNvZnR3YXJlIHNSR0IgSUNDIFByb2ZpbGUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAdGV4dAAAAABDb3B5cmlnaHQgQXJ0aWZleCBTb2Z0d2FyZSAyMDExAFhZWiAAAAAAAADzUQABAAAAARbMWFlaIAAAAAAAAAAAAAAAAAAAAABYWVogAAAAAAAAb6IAADj1AAADkFhZWiAAAAAAAABimQAAt4UAABjaWFlaIAAAAAAAACSgAAAPhAAAts9jdXJ2AAAAAAAABAAAAAAFAAoADwAUABkAHgAjACgALQAyADcAOwBAAEUASgBPAFQAWQBeAGMAaABtAHIAdwB8AIEAhgCLAJAAlQCaAJ8ApACpAK4AsgC3ALwAwQDGAMsA0ADVANsA4ADlAOsA8AD2APsBAQEHAQ0BEwEZAR8BJQErATIBOAE+AUUBTAFSAVkBYAFnAW4BdQF8AYMBiwGSAZoBoQGpAbEBuQHBAckB0QHZAeEB6QHyAfoCAwIMAhQCHQImAi8COAJBAksCVAJdAmcCcQJ6AoQCjgKYAqICrAK2AsECywLVAuAC6wL1AwADCwMWAyEDLQM4A0MDTwNaA2YDcgN+A4oDlgOiA64DugPHA9MD4APsA/kEBgQTBCAELQQ7BEgEVQRjBHEEfgSMBJoEqAS2BMQE0wThBPAE/gUNBRwFKwU6BUkFWAVnBXcFhgWWBaYFtQXFBdUF5QX2BgYGFgYnBjcGSAZZBmoGewaMBp0GrwbABtEG4wb1BwcHGQcrBz0HTwdhB3QHhgeZB6wHvwfSB+UH+AgLCB8IMghGCFoIbgiCCJYIqgi+CNII5wj7CRAJJQk6CU8JZAl5CY8JpAm6Cc8J5Qn7ChEKJwo9ClQKagqBCpgKrgrFCtwK8wsLCyILOQtRC2kLgAuYC7ALyAvhC/kMEgwqDEMMXAx1DI4MpwzADNkM8w0NDSYNQA1aDXQNjg2pDcMN3g34DhMOLg5JDmQOfw6bDrYO0g7uDwkPJQ9BD14Peg+WD7MPzw/sEAkQJhBDEGEQfhCbELkQ1xD1ERMRMRFPEW0RjBGqEckR6BIHEiYSRRJkEoQSoxLDEuMTAxMjE0MTYxODE6QTxRPlFAYUJxRJFGoUixStFM4U8BUSFTQVVhV4FZsVvRXgFgMWJhZJFmwWjxayFtYW+hcdF0EXZReJF64X0hf3GBsYQBhlGIoYrxjVGPoZIBlFGWsZkRm3Gd0aBBoqGlEadxqeGsUa7BsUGzsbYxuKG7Ib2hwCHCocUhx7HKMczBz1HR4dRx1wHZkdwx3sHhYeQB5qHpQevh7pHxMfPh9pH5Qfvx/qIBUgQSBsIJggxCDwIRwhSCF1IaEhziH7IiciVSKCIq8i3SMKIzgjZiOUI8Ij8CQfJE0kfCSrJNolCSU4JWgllyXHJfcmJyZXJocmtyboJxgnSSd6J6sn3CgNKD8ocSiiKNQpBik4KWspnSnQKgIqNSpoKpsqzysCKzYraSudK9EsBSw5LG4soizXLQwtQS12Last4S4WLkwugi63Lu4vJC9aL5Evxy/+MDUwbDCkMNsxEjFKMYIxujHyMioyYzKbMtQzDTNGM38zuDPxNCs0ZTSeNNg1EzVNNYc1wjX9Njc2cjauNuk3JDdgN5w31zgUOFA4jDjIOQU5Qjl/Obw5+To2OnQ6sjrvOy07azuqO+g8JzxlPKQ84z0iPWE9oT3gPiA+YD6gPuA/IT9hP6I/4kAjQGRApkDnQSlBakGsQe5CMEJyQrVC90M6Q31DwEQDREdEikTORRJFVUWaRd5GIkZnRqtG8Ec1R3tHwEgFSEtIkUjXSR1JY0mpSfBKN0p9SsRLDEtTS5pL4kwqTHJMuk0CTUpNk03cTiVObk63TwBPSU+TT91QJ1BxULtRBlFQUZtR5lIxUnxSx1MTU19TqlP2VEJUj1TbVShVdVXCVg9WXFapVvdXRFeSV+BYL1h9WMtZGllpWbhaB1pWWqZa9VtFW5Vb5Vw1XIZc1l0nXXhdyV4aXmxevV8PX2Ffs2AFYFdgqmD8YU9homH1YklinGLwY0Njl2PrZEBklGTpZT1lkmXnZj1mkmboZz1nk2fpaD9olmjsaUNpmmnxakhqn2r3a09rp2v/bFdsr20IbWBtuW4SbmtuxG8eb3hv0XArcIZw4HE6cZVx8HJLcqZzAXNdc7h0FHRwdMx1KHWFdeF2Pnabdvh3VnezeBF4bnjMeSp5iXnnekZ6pXsEe2N7wnwhfIF84X1BfaF+AX5ifsJ/I3+Ef+WAR4CogQqBa4HNgjCCkoL0g1eDuoQdhICE44VHhauGDoZyhteHO4efiASIaYjOiTOJmYn+imSKyoswi5aL/IxjjMqNMY2Yjf+OZo7OjzaPnpAGkG6Q1pE/kaiSEZJ6kuOTTZO2lCCUipT0lV+VyZY0lp+XCpd1l+CYTJi4mSSZkJn8mmia1ZtCm6+cHJyJnPedZJ3SnkCerp8dn4uf+qBpoNihR6G2oiailqMGo3aj5qRWpMelOKWpphqmi6b9p26n4KhSqMSpN6mpqhyqj6sCq3Wr6axcrNCtRK24ri2uoa8Wr4uwALB1sOqxYLHWskuywrM4s660JbSctRO1irYBtnm28Ldot+C4WbjRuUq5wro7urW7LrunvCG8m70VvY++Cr6Evv+/er/1wHDA7MFnwePCX8Lbw1jD1MRRxM7FS8XIxkbGw8dBx7/IPci8yTrJuco4yrfLNsu2zDXMtc01zbXONs62zzfPuNA50LrRPNG+0j/SwdNE08bUSdTL1U7V0dZV1tjXXNfg2GTY6Nls2fHadtr724DcBdyK3RDdlt4c3qLfKd+v4DbgveFE4cziU+Lb42Pj6+Rz5PzlhOYN5pbnH+ep6DLovOlG6dDqW+rl63Dr++yG7RHtnO4o7rTvQO/M8Fjw5fFy8f/yjPMZ86f0NPTC9VD13vZt9vv3ivgZ+Kj5OPnH+lf65/t3/Af8mP0p/br+S/7c/23////bAEMAAwICAgICAwICAgMDAwMEBgQEBAQECAYGBQYJCAoKCQgJCQoMDwwKCw4LCQkNEQ0ODxAQERAKDBITEhATDxAQEP/AAAsIAEQAkQEBEQD/xAAcAAEAAgMBAQEAAAAAAAAAAAAABwgBBQYDBAn/xAA9EAABAwQBAwEEBA0DBQAAAAABAgMEAAUGEQcIEiETFCIxQRUWGCMJJDJRVlhxd5SXsdPVQmG0MzmBkaX/2gAIAQEAAD8A/VOlKUpSlKUpUdcx874PwdDs8rMWb5Jcv0xcGBFs1ofuMl51DSnV6ZYSpeghCiTrQ15qN/t18TfoRy1/Lq7f2afbr4m/Qjlr+XV2/s0+3XxN+hHLX8urt/Zp9uvib9COWv5dXb+zUm8R814vzPCuM7GLNlVvRbHW2XU37H5VrUsrSSC2mQhJWPB2U71438RUgUpSlKUpSlKVXy8sM571t4/GMdl+PxTg0u6F9JQTHn3qQI7SNhfclXs0GQdFOu1wHfvCpmzXJfqZi9wydOO3y/GA0HBbrLG9pmySVABDTfckKV5+ZAABJOhUS9PvUndObuR+U8Cu3GVww1zjaTa4qmrjcGX5by5TLrivUTHUtlvt9Ma7HXNhWyQRqvO9c+Z7k3LmUcQ8EYHYMjl4LDivZHdL5kL1vhx5UkKUzCa9CM+px7sT3qJCUpHgnu8V2PAfNti56wdzKrZa5lmuVtuMuyX2yzHUrk2m5xXC2/GcKCUq0dKSoa7kKSdJJKRJIGvz/wDus0pSlKUpSlKwo6SSKr30usnKc85t5ikJSVZBm7uP25aFhaTbbOyiGjtUUhQ3I9rUU7KQT4+e7BuAFCgRvxVROkvX2verjfw+nsc/4T9a7oJltSeYeqdF2ZnfWVHJz/tTspCk91u+9TBSnfjQSl7WgPdUg7II19f4OfXZ1DfvuyT+jNXDpXNcg5fcMIxt2+WrB8gy2UlaWmrZZG2VSXFK3o/fONoSkHW1FXje9Gox6VOoq9dRNsz6dfcHRisjDM0n4oYPtyZbn4shoqU44j7vv7lqB9MqR48KUPJnOob6kee8i4Kw+65LYeH8izD6Ls0y8Pyoz8WLbobTDa1q9ofdcCwfdHuNtrUQfdBPiun4n5Hl8jcI4nyvLtjMKTkeNQ765EbcK22VvRkulsKI2QCdbI3VfeE+rvqb5qdxtuH0Zz7Darw3AlyMnueSJRbUw3m231Psp9AOPdzS/u0pJ99SUrI7V6t9+2vJiZElLfajSWnVxnPReShYUW3O1Ku1QH5J7VJOj50oH5isLmw2pbUFyUyiS+hbjTKnAFuJR295Sn4kDuTsj4dw38RXvSuZ5OzJnjrjfK+QZLSnWcYsk68uISjvUpMZhbpATsdxPZ8Njf5xXDdI2FXDj/ptwDHLz7T9KKtCLlcvaVuKd9tmqVLk95c9/fqyHPCvI+HyqTsihXa5WG4W+w3kWm4yIzjUSeYyZHszpSQlz0lkJc7To9pOjrVV54k6UOReKuU8m5Qb6h5l3kZzcolwyiLIxaE2icI4WltttSF7YT2LUnaQToA+TsneS+nfMsP5ey/l7g7P7RYJGfxmE5Dab3ZXLhCdmsIKGZrPoyGFtuAHS0kqSvavgTsdf0+8HWngPA14nDvMi+3S43KZe75fJTKGpF2uUp0uPSHEo90HylIA+CUJGydkyZSsKAI8jfkVT38HP+R1DfvuyT+jNXC351UN9ZYH2TuXzrz9Srx/xV1pun/JMcxDoe47yfL7u3a7LbeN7VInzXEKUmOwmA33LISCogDzoDdV2zd2/wDSj0pYR1E8N9QORcgQsZj2aHIZuVxQmyXuzKKI3pMwFACMpADYQWj6w7FFwuHvNX7s9xbvFqh3VttSETI7chKVEEgLSFAHXj4GqpdUkmR01ZzA6huJJgk5ZmM6LZbvx+C659eSkBCFRm20rW1NYb0Q+ElHpjtX8QFbro/sds5UjHqtzXKoOWZ7kTTkDsjoWiLiMdKvfs8Zl0BbLiFf9ZawHHFeT7pBVZ4nQ3VSeLeqrK8862r9xPcrZNs2EyMOVOxZFwirYeub8acpt+YlC2wtKXB6wSFkfdx21gfeV2fW5JXduJ7XxRDWEzeUMqs2It7ShYTHelJdmLKFEd6RFYf2AQfIqwDDTbLKGmUBLaAAhKRoBI+AH/iobX1E5SlakjpX5mUASNiFZ9H/AOjWPtFZT+qrzP8AwVn/AMjT7RWU/qq8z/wVn/yNPtFZT+qrzP8AwVn/AMjUv2qa5crZEuLtvlQFymG3lRZQSHmCpIJbcCFKSFp3o6URsHRI819VaTM7Nfr/AI1MtGMZbJxi5v8AZ6F1jRGJTkfS0qVpp9Km1dyQU+8k6CiR5ANQxwH0r3zgTI7zdbVzfkF3tmTXydkt9tUyz21tudcZSO1x71W2g40AoIUENqSkFOtaJB1nEWH3iydX/LF3sHIuVX/GZdviOXqBdpKnYdsvjy0uMxoexoBuIO5YHhKZEdO1H8iRefeHb7zdiMnBYnJ91xOy3aDMtt6jwLbCkm4R5CAgoK5Da1NFKe8AtlJ98n5DWhwjpoFi4Xu3Aebck3nMMQm2BrGYUeTAhw3bfAQwpjtQ5HbSXFFBQe9zuILYPzVvkbr0g5hn1oxbj3mTmeFlPHWLTGJacfh4iza37iIySIjUuS2+pJQjx3JZZaC9f6R4FmW2kMtpaaSEIQAlISNAD8wFR5Z+DcVgcwXvm+7S597yW4x27fbV3BwONWOAltIXGhI1poOLC3HFeVKK9E9o0fO0cFYzjXMdx5jxO53KySsghljIbTDWgW68SEkejMeaKTqQgdyfUQUlQV729HclVS7q6fXxr1h9NHMrLgjx7jdJuD3R0pf7XmZiUhhtZRtOkrdcUhJHlY2dhJ1JnIUwZj1jcV4EHFLawnHrznc2P3Ds9Z0JtsNagpBCtetN7e1QII2R4G7Cfsql2WdS/VHZurW3dLFux7ilcq/Wp7ILfdnzcvTbgp9oKUvNpVsvfi6gQn3TsHY3oW+eRfxjjnom2C+exHsUtDnsntfp+CQD3+n3/Lfd2/71UvgbqW6keUuo/N+DshxvjODE41ksovs6Gq4LcltuK0n2VK1aSopBJLnhJ0Pe3seCOpXqfV1aJ6WU2LitUpNnGQvXbtuSUJhb/IS33kqd0QPiE+Sfl2m5wrNKUpSlKUpVSvwn+Oz53SvPzezBX0rx9fLVlMFbaHC604zIDaloLZBQUpeUor/0pSo+PiOg6XL5F5a5S5X59gPIetl2XY8ZtLqEOoS4xCt6JD60hZ12mVPeQNAH7rz5JqytUMzz/vB8dfu0f/pcqujkOcY/jt/x7FLhJV9J5S/Ij29hCe4q9COt51avPhCUpGz58rQNeaoDwPYeTL919dT7XGvIdrxN9qZAVLcn46LsJCDsJSke0M+no7O9q3v5ar7ePLVmtm/CwPws+y+Dkt2HG6lGdDs4tjZbJR2o9H1XfI8+93+d/Aar9E6UpSlKUpSlcZzPgTfKPEuY8dLQyVZHY5ttbLyO5CHXWVJbWRsb7VlKviPh8ajnoe4Tu3T/ANNGIcdZNbEQchZafm3ptKm1kTH3luKSVtqUhfakoQFJOiECp4qqWTdGvJeQdQsPqUZ6iGomVWq3vWa2oGGR3I7EBaniG1oMgeosCQseoSCdDx41XUW3pu5Vl8p2zlnPuomTkFwx2z3G3WOAxjMeFAhyJbfpqlLaS6v1Vga2CRsJA2BsHRcQ9Hue8U825LzYnnpF1n5vJjvZNEXiTDLcxDW9IaUHyWN7/KAV+yvka6NuTG+oQ9SZ6iGVZSu3CyrR9TI4jmB3A+n2e0eF6GvU3v8A2+VWtrNKUpSlKUpSlKUpSlK//9k=

 

donde:

LH es el horizonte de liquidez del factor de riesgo no modelizable a que se refiere el artículo 325 ter quinquies del Reglamento (UE) n.o 575/2013;

d)

las perturbaciones calibradas a la baja y al alza serán el resultado de la letra c).

4.   Cuando el factor de riesgo no modelizable no cumpla las condiciones establecidas en los apartados 2 y 3, las entidades determinarán las correspondientes perturbaciones calibradas a la baja y al alza seleccionando un factor de riesgo que cumpla las condiciones establecidas en el apartado 5 y aplicando el método establecido en el apartado 6 al factor de riesgo así seleccionado.

5.   El factor de riesgo que se seleccione de conformidad con el apartado 4 deberá cumplir todas las condiciones siguientes:

a)

pertenecerá a la misma categoría general y subcategoría general de factores de riesgo a que se refiere el artículo 325 ter quinquies del Reglamento (UE) n.o 575/2013 que el factor de riesgo no modelizable;

b)

será de la misma naturaleza que el factor de riesgo no modelizable;

c)

diferirá del factor de riesgo no modelizable en características que no den lugar a una subestimación de la volatilidad del factor de riesgo no modelizable, incluso en condiciones de tensión;

d)

su serie temporal de rendimientos de diez días hábiles determinada con arreglo al apartado 6, letra a), contendrá al menos 12 rendimientos.

6.   Con arreglo al método a que se refiere el apartado 4, las entidades realizarán las operaciones que a continuación se indican en el siguiente orden:

a)

determinarán, en relación con el factor de riesgo seleccionado y de conformidad con el artículo 7, la serie temporal de rendimientos de diez días hábiles en el período de tensión determinado de conformidad con el artículo 12;

b)

determinarán las perturbaciones calibradas a la baja y al alza en relación con el factor de riesgo seleccionado mediante:

i)

el método histórico establecido en el artículo 8, cuando el número de rendimientos en la serie temporal de diez días hábiles del factor de riesgo seleccionado a que se refiere la letra a) del presente apartado sea igual o superior a 200;

ii)

el método sigma asimétrico establecido en el artículo 9, cuando el número de rendimientos en la serie temporal de diez días hábiles del factor de riesgo seleccionado a que se refiere la letra a) del presente apartado sea inferior a 200;

c)

determinarán la perturbación calibrada a la baja respecto del factor de riesgo no modelizable multiplicando la perturbación a la baja correspondiente al factor de riesgo seleccionado determinada de conformidad con la letra b) por

 

Imagen: data:image/jpg;base64,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

 

donde:

 

Imagen: data:image/jpg;base64,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 es uno de los siguientes números, dependiendo del método utilizado para determinar la perturbación calibrada a la baja respecto del factor de riesgo seleccionado de conformidad con la letra b):

 

i)

el número de rendimientos incluidos en la serie temporal de diez días hábiles del factor de riesgo seleccionado a que se refiere la letra a), cuando la entidad haya utilizado el método histórico para determinar la perturbación calibrada a la baja respecto del factor de riesgo seleccionado;

ii)

el número de rendimientos incluidos en el subconjunto determinado de conformidad con el artículo 9, apartado 1, letra a), inciso i), cuando la entidad haya utilizado el método sigma asimétrico para determinar la perturbación calibrada a la baja respecto del factor de riesgo seleccionado;

d)

determinarán la perturbación calibrada al alza respecto del factor de riesgo no modelizable multiplicando la perturbación al alza correspondiente al factor de riesgo seleccionado determinada de conformidad con la letra b) por

 

Imagen: data:image/jpg;base64,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

 

donde:

 

Imagen: data:image/jpg;base64,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 es uno de los siguientes números, dependiendo del método utilizado para determinar la perturbación calibrada al alza respecto del factor de riesgo seleccionado de conformidad con la letra b):

 

i)

el número de rendimientos incluidos en la serie temporal de diez días hábiles del factor de riesgo seleccionado a que se refiere la letra a), cuando la entidad haya utilizado el método histórico para determinar la perturbación calibrada al alza respecto del factor de riesgo seleccionado;

ii)

el número de rendimientos incluidos en el subconjunto determinado de conformidad con el artículo 9, apartado 1, letra a), inciso ii), cuando la entidad haya utilizado el método sigma asimétrico para determinar la perturbación calibrada al alza respecto del factor de riesgo seleccionado.

7.   No obstante lo dispuesto en el apartado 6, letra b), incisos i) y ii), cuando las entidades apliquen el método a que se refiere el apartado 4 a todos los factores de riesgo no modelizables de un segmento estándar no modelizable, determinarán las perturbaciones al alza y a la baja en relación con todos los correspondientes factores de riesgo seleccionados de conformidad con uno de los métodos siguientes:

a)

el método histórico establecido en el artículo 8, cuando el número de rendimientos en la serie temporal de diez días hábiles a que se refiere el apartado 6, letra a), sea igual o superior a 200 para todos los factores de riesgo seleccionados;

b)

el método sigma asimétrico establecido en el artículo 9, cuando no se cumpla la condición indicada en la letra a) del presente apartado para aplicar el método histórico.

Artículo 11

Estimadores de la pérdida esperada condicional

1.   Las entidades calcularán la estimación de la pérdida esperada condicional de la cola izquierda de una serie temporal X con arreglo a la siguiente fórmula:

 

Imagen: data:image/jpg;base64,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

 

donde:

N es el número de observaciones de la serie temporal;

α = 2,5 %;

 

Imagen: data:image/jpg;base64,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 ] representa la parte entera del producto Imagen: data:image/jpg;base64,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 ;

 

 

Imagen: data:image/jpg;base64,/9j/4AAQSkZJRgABAQABLAEsAAD/4gogSUNDX1BST0ZJTEUAAQEAAAoQAAAAAAIQAABtbnRyUkdCIFhZWiAAAAAAAAAAAAAAAABhY3NwQVBQTAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA9tYAAQAAAADTLQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAApkZXNjAAAA/AAAAHxjcHJ0AAABeAAAACh3dHB0AAABoAAAABRia3B0AAABtAAAABRyWFlaAAAByAAAABRnWFlaAAAB3AAAABRiWFlaAAAB8AAAABRyVFJDAAACBAAACAxnVFJDAAACBAAACAxiVFJDAAACBAAACAxkZXNjAAAAAAAAACJBcnRpZmV4IFNvZnR3YXJlIHNSR0IgSUNDIFByb2ZpbGUAAAAAAAAAAAAAACJBcnRpZmV4IFNvZnR3YXJlIHNSR0IgSUNDIFByb2ZpbGUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAdGV4dAAAAABDb3B5cmlnaHQgQXJ0aWZleCBTb2Z0d2FyZSAyMDExAFhZWiAAAAAAAADzUQABAAAAARbMWFlaIAAAAAAAAAAAAAAAAAAAAABYWVogAAAAAAAAb6IAADj1AAADkFhZWiAAAAAAAABimQAAt4UAABjaWFlaIAAAAAAAACSgAAAPhAAAts9jdXJ2AAAAAAAABAAAAAAFAAoADwAUABkAHgAjACgALQAyADcAOwBAAEUASgBPAFQAWQBeAGMAaABtAHIAdwB8AIEAhgCLAJAAlQCaAJ8ApACpAK4AsgC3ALwAwQDGAMsA0ADVANsA4ADlAOsA8AD2APsBAQEHAQ0BEwEZAR8BJQErATIBOAE+AUUBTAFSAVkBYAFnAW4BdQF8AYMBiwGSAZoBoQGpAbEBuQHBAckB0QHZAeEB6QHyAfoCAwIMAhQCHQImAi8COAJBAksCVAJdAmcCcQJ6AoQCjgKYAqICrAK2AsECywLVAuAC6wL1AwADCwMWAyEDLQM4A0MDTwNaA2YDcgN+A4oDlgOiA64DugPHA9MD4APsA/kEBgQTBCAELQQ7BEgEVQRjBHEEfgSMBJoEqAS2BMQE0wThBPAE/gUNBRwFKwU6BUkFWAVnBXcFhgWWBaYFtQXFBdUF5QX2BgYGFgYnBjcGSAZZBmoGewaMBp0GrwbABtEG4wb1BwcHGQcrBz0HTwdhB3QHhgeZB6wHvwfSB+UH+AgLCB8IMghGCFoIbgiCCJYIqgi+CNII5wj7CRAJJQk6CU8JZAl5CY8JpAm6Cc8J5Qn7ChEKJwo9ClQKagqBCpgKrgrFCtwK8wsLCyILOQtRC2kLgAuYC7ALyAvhC/kMEgwqDEMMXAx1DI4MpwzADNkM8w0NDSYNQA1aDXQNjg2pDcMN3g34DhMOLg5JDmQOfw6bDrYO0g7uDwkPJQ9BD14Peg+WD7MPzw/sEAkQJhBDEGEQfhCbELkQ1xD1ERMRMRFPEW0RjBGqEckR6BIHEiYSRRJkEoQSoxLDEuMTAxMjE0MTYxODE6QTxRPlFAYUJxRJFGoUixStFM4U8BUSFTQVVhV4FZsVvRXgFgMWJhZJFmwWjxayFtYW+hcdF0EXZReJF64X0hf3GBsYQBhlGIoYrxjVGPoZIBlFGWsZkRm3Gd0aBBoqGlEadxqeGsUa7BsUGzsbYxuKG7Ib2hwCHCocUhx7HKMczBz1HR4dRx1wHZkdwx3sHhYeQB5qHpQevh7pHxMfPh9pH5Qfvx/qIBUgQSBsIJggxCDwIRwhSCF1IaEhziH7IiciVSKCIq8i3SMKIzgjZiOUI8Ij8CQfJE0kfCSrJNolCSU4JWgllyXHJfcmJyZXJocmtyboJxgnSSd6J6sn3CgNKD8ocSiiKNQpBik4KWspnSnQKgIqNSpoKpsqzysCKzYraSudK9EsBSw5LG4soizXLQwtQS12Last4S4WLkwugi63Lu4vJC9aL5Evxy/+MDUwbDCkMNsxEjFKMYIxujHyMioyYzKbMtQzDTNGM38zuDPxNCs0ZTSeNNg1EzVNNYc1wjX9Njc2cjauNuk3JDdgN5w31zgUOFA4jDjIOQU5Qjl/Obw5+To2OnQ6sjrvOy07azuqO+g8JzxlPKQ84z0iPWE9oT3gPiA+YD6gPuA/IT9hP6I/4kAjQGRApkDnQSlBakGsQe5CMEJyQrVC90M6Q31DwEQDREdEikTORRJFVUWaRd5GIkZnRqtG8Ec1R3tHwEgFSEtIkUjXSR1JY0mpSfBKN0p9SsRLDEtTS5pL4kwqTHJMuk0CTUpNk03cTiVObk63TwBPSU+TT91QJ1BxULtRBlFQUZtR5lIxUnxSx1MTU19TqlP2VEJUj1TbVShVdVXCVg9WXFapVvdXRFeSV+BYL1h9WMtZGllpWbhaB1pWWqZa9VtFW5Vb5Vw1XIZc1l0nXXhdyV4aXmxevV8PX2Ffs2AFYFdgqmD8YU9homH1YklinGLwY0Njl2PrZEBklGTpZT1lkmXnZj1mkmboZz1nk2fpaD9olmjsaUNpmmnxakhqn2r3a09rp2v/bFdsr20IbWBtuW4SbmtuxG8eb3hv0XArcIZw4HE6cZVx8HJLcqZzAXNdc7h0FHRwdMx1KHWFdeF2Pnabdvh3VnezeBF4bnjMeSp5iXnnekZ6pXsEe2N7wnwhfIF84X1BfaF+AX5ifsJ/I3+Ef+WAR4CogQqBa4HNgjCCkoL0g1eDuoQdhICE44VHhauGDoZyhteHO4efiASIaYjOiTOJmYn+imSKyoswi5aL/IxjjMqNMY2Yjf+OZo7OjzaPnpAGkG6Q1pE/kaiSEZJ6kuOTTZO2lCCUipT0lV+VyZY0lp+XCpd1l+CYTJi4mSSZkJn8mmia1ZtCm6+cHJyJnPedZJ3SnkCerp8dn4uf+qBpoNihR6G2oiailqMGo3aj5qRWpMelOKWpphqmi6b9p26n4KhSqMSpN6mpqhyqj6sCq3Wr6axcrNCtRK24ri2uoa8Wr4uwALB1sOqxYLHWskuywrM4s660JbSctRO1irYBtnm28Ldot+C4WbjRuUq5wro7urW7LrunvCG8m70VvY++Cr6Evv+/er/1wHDA7MFnwePCX8Lbw1jD1MRRxM7FS8XIxkbGw8dBx7/IPci8yTrJuco4yrfLNsu2zDXMtc01zbXONs62zzfPuNA50LrRPNG+0j/SwdNE08bUSdTL1U7V0dZV1tjXXNfg2GTY6Nls2fHadtr724DcBdyK3RDdlt4c3qLfKd+v4DbgveFE4cziU+Lb42Pj6+Rz5PzlhOYN5pbnH+ep6DLovOlG6dDqW+rl63Dr++yG7RHtnO4o7rTvQO/M8Fjw5fFy8f/yjPMZ86f0NPTC9VD13vZt9vv3ivgZ+Kj5OPnH+lf65/t3/Af8mP0p/br+S/7c/23////bAEMAAwICAgICAwICAgMDAwMEBgQEBAQECAYGBQYJCAoKCQgJCQoMDwwKCw4LCQkNEQ0ODxAQERAKDBITEhATDxAQEP/AAAsIACUALgEBEQD/xAAcAAABBAMBAAAAAAAAAAAAAAAAAQUGCAMHCQT/xAAsEAABAwQCAgECBQUAAAAAAAABAgMEBQYHEQASCCETFDEJFRYiIzJBQkNh/9oACAEBAAA/AOml83zbuObZl3fdbs5qlwepfXCpsme6kKUEg/DGbcdUAT7ISQkbJ0ATzX+J/LTAOcUV1zFV7SK+m2Yv1lULNDqDf07f7vX8jCe6z1VptO1nR0k8xYm8vvHzOdxu2niu9pldqcdC1vtpt+pMNsBH9QcdejobbV/bqpQUT6A3zcnDhxCNjXOaflBPuTwJ8hpOSMQV6jUu186sOxK1Tpix8NDq6VoSKylhI2ptBfLhA/aVKdSoju3q/GHMe2xjDHVHtK05i58NlkyHKk678rtTkPEuPTXXNn5HHnFqcUrZ339egOPRvW1Bd4sD9QQjcX5aqsGmB0GQmEl1LRfUn/FHdQSCdbIOt9TrFMyBZVPrFAoE256czPun5/yVlT6d1AsoC3QyfsspQe2gd9QSAQDqQcj1+XXLsq15dxQbPr10PxugRS6Gy05MfKlBP7EuuNo0N7JKhoAn39uVfsLFE7P1CzDfPkviS5oNZu1l6gQaLNZYLlOt5n+WLHgKS6sF9bqQ+6vaEqfDQ66bBLR4M3X5EYvtiPgrMWEshSaPS6kYFrXQ7GiaRSlLIbTObEgrZ+MaIKfk0lXT/WO0m8fPqsh+P+UcyKpFLqlw5OrVxuy4tZUtEcwojz1PiwHXWUlwstxY3XaU7244QNqJLVNZt68/w1Yt52tbcez/ANOWUL0tuNDeck/k06mpVMill14lwlK2QkqJ2UrWDsEg2jxtdS76x5bF7ORPpVXBRoVVLHft8RfYQ6UdtDeu+t6H25IyAfRG+AAHoAcQoTr0kb+49crthrH9xY9F9+NdQZqNKtydKqtds6v0ppBDVNnyFOPxCtxK0olRn5C+vyJV3bcbUnt1WEtWR8O1qyPHGneIOH5lw1Zd1RH7aj1arBpxFGoitfWPSXW2kIKUMOKZaR1+Ra3UD2EqWmyNAotPtuh0+3qTFajQaZFahxmWkBKGmm0BCEpA9ABKQAP+c9/DhxOHF5//2Q== representa la i-ésima observación más pequeña de la serie temporal X.

 

2.   Las entidades calcularán la estimación de la pérdida esperada condicional de la cola derecha de una serie temporal X con arreglo a la siguiente fórmula:

 

Imagen: data:image/jpg;base64,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

 

donde:

 

Imagen: data:image/jpg;base64,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: data:image/jpg;base64,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 ) es la estimación de la pérdida esperada condicional de la cola izquierda para la serie temporal  Imagen: data:image/jpg;base64,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 calculada de conformidad con el apartado 1.

 

Artículo 12

Determinación del período de tensión

1.   Las entidades determinarán el período de tensión para los factores de riesgo no modelizables de una categoría general de factores de riesgo identificando el período de observación de doce meses que maximice el valor obtenido con arreglo a la siguiente fórmula:

 

Imagen: data:image/jpg;base64,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

 

donde:

i representa la categoría general de factores de riesgo;

j es el índice que designa los factores de riesgo no modelizables o los segmentos estándar no modelizables que pertenecen a la categoría general de factores de riesgo i y para los que la entidad calcula la medida del riesgo en un supuesto de tensión;

 

Imagen: data:image/jpg;base64,/9j/4AAQSkZJRgABAQABLAEsAAD/4gogSUNDX1BST0ZJTEUAAQEAAAoQAAAAAAIQAABtbnRyUkdCIFhZWiAAAAAAAAAAAAAAAABhY3NwQVBQTAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA9tYAAQAAAADTLQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAApkZXNjAAAA/AAAAHxjcHJ0AAABeAAAACh3dHB0AAABoAAAABRia3B0AAABtAAAABRyWFlaAAAByAAAABRnWFlaAAAB3AAAABRiWFlaAAAB8AAAABRyVFJDAAACBAAACAxnVFJDAAACBAAACAxiVFJDAAACBAAACAxkZXNjAAAAAAAAACJBcnRpZmV4IFNvZnR3YXJlIHNSR0IgSUNDIFByb2ZpbGUAAAAAAAAAAAAAACJBcnRpZmV4IFNvZnR3YXJlIHNSR0IgSUNDIFByb2ZpbGUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAdGV4dAAAAABDb3B5cmlnaHQgQXJ0aWZleCBTb2Z0d2FyZSAyMDExAFhZWiAAAAAAAADzUQABAAAAARbMWFlaIAAAAAAAAAAAAAAAAAAAAABYWVogAAAAAAAAb6IAADj1AAADkFhZWiAAAAAAAABimQAAt4UAABjaWFlaIAAAAAAAACSgAAAPhAAAts9jdXJ2AAAAAAAABAAAAAAFAAoADwAUABkAHgAjACgALQAyADcAOwBAAEUASgBPAFQAWQBeAGMAaABtAHIAdwB8AIEAhgCLAJAAlQCaAJ8ApACpAK4AsgC3ALwAwQDGAMsA0ADVANsA4ADlAOsA8AD2APsBAQEHAQ0BEwEZAR8BJQErATIBOAE+AUUBTAFSAVkBYAFnAW4BdQF8AYMBiwGSAZoBoQGpAbEBuQHBAckB0QHZAeEB6QHyAfoCAwIMAhQCHQImAi8COAJBAksCVAJdAmcCcQJ6AoQCjgKYAqICrAK2AsECywLVAuAC6wL1AwADCwMWAyEDLQM4A0MDTwNaA2YDcgN+A4oDlgOiA64DugPHA9MD4APsA/kEBgQTBCAELQQ7BEgEVQRjBHEEfgSMBJoEqAS2BMQE0wThBPAE/gUNBRwFKwU6BUkFWAVnBXcFhgWWBaYFtQXFBdUF5QX2BgYGFgYnBjcGSAZZBmoGewaMBp0GrwbABtEG4wb1BwcHGQcrBz0HTwdhB3QHhgeZB6wHvwfSB+UH+AgLCB8IMghGCFoIbgiCCJYIqgi+CNII5wj7CRAJJQk6CU8JZAl5CY8JpAm6Cc8J5Qn7ChEKJwo9ClQKagqBCpgKrgrFCtwK8wsLCyILOQtRC2kLgAuYC7ALyAvhC/kMEgwqDEMMXAx1DI4MpwzADNkM8w0NDSYNQA1aDXQNjg2pDcMN3g34DhMOLg5JDmQOfw6bDrYO0g7uDwkPJQ9BD14Peg+WD7MPzw/sEAkQJhBDEGEQfhCbELkQ1xD1ERMRMRFPEW0RjBGqEckR6BIHEiYSRRJkEoQSoxLDEuMTAxMjE0MTYxODE6QTxRPlFAYUJxRJFGoUixStFM4U8BUSFTQVVhV4FZsVvRXgFgMWJhZJFmwWjxayFtYW+hcdF0EXZReJF64X0hf3GBsYQBhlGIoYrxjVGPoZIBlFGWsZkRm3Gd0aBBoqGlEadxqeGsUa7BsUGzsbYxuKG7Ib2hwCHCocUhx7HKMczBz1HR4dRx1wHZkdwx3sHhYeQB5qHpQevh7pHxMfPh9pH5Qfvx/qIBUgQSBsIJggxCDwIRwhSCF1IaEhziH7IiciVSKCIq8i3SMKIzgjZiOUI8Ij8CQfJE0kfCSrJNolCSU4JWgllyXHJfcmJyZXJocmtyboJxgnSSd6J6sn3CgNKD8ocSiiKNQpBik4KWspnSnQKgIqNSpoKpsqzysCKzYraSudK9EsBSw5LG4soizXLQwtQS12Last4S4WLkwugi63Lu4vJC9aL5Evxy/+MDUwbDCkMNsxEjFKMYIxujHyMioyYzKbMtQzDTNGM38zuDPxNCs0ZTSeNNg1EzVNNYc1wjX9Njc2cjauNuk3JDdgN5w31zgUOFA4jDjIOQU5Qjl/Obw5+To2OnQ6sjrvOy07azuqO+g8JzxlPKQ84z0iPWE9oT3gPiA+YD6gPuA/IT9hP6I/4kAjQGRApkDnQSlBakGsQe5CMEJyQrVC90M6Q31DwEQDREdEikTORRJFVUWaRd5GIkZnRqtG8Ec1R3tHwEgFSEtIkUjXSR1JY0mpSfBKN0p9SsRLDEtTS5pL4kwqTHJMuk0CTUpNk03cTiVObk63TwBPSU+TT91QJ1BxULtRBlFQUZtR5lIxUnxSx1MTU19TqlP2VEJUj1TbVShVdVXCVg9WXFapVvdXRFeSV+BYL1h9WMtZGllpWbhaB1pWWqZa9VtFW5Vb5Vw1XIZc1l0nXXhdyV4aXmxevV8PX2Ffs2AFYFdgqmD8YU9homH1YklinGLwY0Njl2PrZEBklGTpZT1lkmXnZj1mkmboZz1nk2fpaD9olmjsaUNpmmnxakhqn2r3a09rp2v/bFdsr20IbWBtuW4SbmtuxG8eb3hv0XArcIZw4HE6cZVx8HJLcqZzAXNdc7h0FHRwdMx1KHWFdeF2Pnabdvh3VnezeBF4bnjMeSp5iXnnekZ6pXsEe2N7wnwhfIF84X1BfaF+AX5ifsJ/I3+Ef+WAR4CogQqBa4HNgjCCkoL0g1eDuoQdhICE44VHhauGDoZyhteHO4efiASIaYjOiTOJmYn+imSKyoswi5aL/IxjjMqNMY2Yjf+OZo7OjzaPnpAGkG6Q1pE/kaiSEZJ6kuOTTZO2lCCUipT0lV+VyZY0lp+XCpd1l+CYTJi4mSSZkJn8mmia1ZtCm6+cHJyJnPedZJ3SnkCerp8dn4uf+qBpoNihR6G2oiailqMGo3aj5qRWpMelOKWpphqmi6b9p26n4KhSqMSpN6mpqhyqj6sCq3Wr6axcrNCtRK24ri2uoa8Wr4uwALB1sOqxYLHWskuywrM4s660JbSctRO1irYBtnm28Ldot+C4WbjRuUq5wro7urW7LrunvCG8m70VvY++Cr6Evv+/er/1wHDA7MFnwePCX8Lbw1jD1MRRxM7FS8XIxkbGw8dBx7/IPci8yTrJuco4yrfLNsu2zDXMtc01zbXONs62zzfPuNA50LrRPNG+0j/SwdNE08bUSdTL1U7V0dZV1tjXXNfg2GTY6Nls2fHadtr724DcBdyK3RDdlt4c3qLfKd+v4DbgveFE4cziU+Lb42Pj6+Rz5PzlhOYN5pbnH+ep6DLovOlG6dDqW+rl63Dr++yG7RHtnO4o7rTvQO/M8Fjw5fFy8f/yjPMZ86f0NPTC9VD13vZt9vv3ivgZ+Kj5OPnH+lf65/t3/Af8mP0p/br+S/7c/23////bAEMAAwICAgICAwICAgMDAwMEBgQEBAQECAYGBQYJCAoKCQgJCQoMDwwKCw4LCQkNEQ0ODxAQERAKDBITEhATDxAQEP/AAAsIACIAOgEBEQD/xAAbAAACAgMBAAAAAAAAAAAAAAAABQYHAggJAf/EACsQAAEEAgICAgEDBAMAAAAAAAIBAwQFBgcAEQgSEyEUCRUjFyIxQWGBsf/aAAgBAQAAPwDqnw4cOHDkTqdp4HebDvtU1V+D+U4zEizrWAjDqLGZkoqskpqKAXsid9CSqn12id8lnE2Xt5c9jk1vBLCog3xCP4T9vDdlRAL3Tv5GmnGjJFH2ROjHpVRftE6XTnxi8jfMbyaxLMcho5OmaediN+/j/wCDKorU2pbzQAan84ze2gX367+I1Trvr/XLW8c/LdncC7DxbNcNdxXNdVzHYmRVjUhZTJth8iJIjOEIEbZKy50hCi9eq9qhIvEWudi+UW9NdVm/tbX2v66ptiflUuHT6114psFHDbAJdk3IX4JRenf8bag0S+hiaiq8S415b7Jm+Pupcgk0lKGyNuZLKxyE1YgTFbVvhNkgf5AoYuH8LTCAjYkhuuIgp6qX002DnXlbpfLdeVd/keHZfiubZxU0cy5jUblfNqhkOL7sEx8rjZtOeig297CYESISGpCvLAxa3zOB5WZdh1nmku3oJWHVuQQIEmFEb/bHXJ0pg2m3WmhdcbVGUJEdI1RSLpfvl2cxP/H/AGn/ALzmV+ndS78tcD3L/RzP8LoAXPbRv4r3G5Fg4UtWQ9TF5uU2LYfYJ0rTnSoq9Ei+vLW/Tgd15a6Rz/at03KnZncX1k3saxmupKWVLYFTNGxABQY6tuqQtIPafISdr0PUNxzxC8kdYYyzmfgf5PnHwXJAbyWsxPJoKKyjT4i800Bug4goYGiF2DRfQoSqv2kmkw9cec/jbrrEdgQpers7tL6zGoSmgEH7ZkFar5TTBE69AJBdNRIhL2Xr2UxQlTvH5o+KmZ4ce89hU26dW3WQ1+OpKfrASypZTrvxwp6oQe3uh+iqROOdkvr7ISifNk9Mak2/SbGtNo7mzegvLeTjkDGWRp4LjDZtxpD75SSQukAnDkKnxiiiKAioS9qiXlxLmNRfX2NzanGcqfxuzkCCR7RiIzKOMqGKqqNPCTZdiij/AHIvXt2n2ico7xl8RZXjLYW6Y/uG7uqa/nyLeyq51VBAX57oiKvI62COB0gJ0Aqg/wDHInhngbM13MzPHsM3LNga9zTJmsokY8lYf5MV1tCNI7UwZA9Mk78Cn/F7m0wLREqERK/1z4zb81Br2u1br/ymBaGurm4Md28wtqfOgkgqhlFeGS2ItoSqTbb4P/H0g+xiiDzGz8IaePhGr8M19s/IsSc1layr1i5Yaak2NhYPtOib7xuorZKbrpG4JAQmCq30KL2jmf447I2Je4lK3xuiBlNFh1ozeRqWlxZKdmfYsovwPTTKS+TotkqmLQfGCkvZISIKJsAidJ1z3hw4cOHDhw5//9k= es la medida del riesgo en un supuesto de tensión reajustada en relación con el factor de riesgo no modelizable o el segmento estándar no modelizable j, calculada de conformidad con el artículo 16.

 

2.   No obstante lo dispuesto en el apartado 1, las entidades podrán determinar el período de tensión para los factores de riesgo no modelizables de una categoría general de factores de riesgo identificando el período de observación de doce meses que maximice la medida de la pérdida esperada condicional parcial

 

Imagen: data:image/jpg;base64,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

 

a que se refiere el artículo 325 ter ter, apartado 1, del Reglamento (UE) n.o 575/2013. Cuando las entidades apliquen esta excepción, aportarán pruebas de que el período de tensión identificado representa un período de tensión financiera para sus factores de riesgo no modelizables. Las entidades tendrán en cuenta el modo en que su cartera está expuesta a los factores de riesgo no modelizables de la categoría general de factores de riesgo.

3.   Cuando determinen el período de tensión, las entidades deberán valerse de un período de observación que comience al menos el 1 de enero de 2007 y satisfaga a las autoridades competentes.

4.   Las entidades revisarán el período de tensión identificado al menos trimestralmente.

Artículo 13

Cómputo de las pérdidas

1.   Las entidades calcularán la pérdida correspondiente a un supuesto de perturbación futura aplicado a uno o varios factores de riesgo no modelizables calculando la pérdida que se produce en la cartera de posiciones para la que calculen los requisitos de fondos propios por riesgo de mercado de conformidad con el método de modelos internos alternativos establecido en la parte tercera, título IV, capítulo 1 ter, del Reglamento (UE) n.o 575/2013 si ese supuesto de perturbación futura se aplica a ese factor de riesgo no modelizable o a esos factores de riesgo no modelizables de un segmento estándar, y todos los demás factores de riesgo se mantienen inalterados.

2.   Las entidades calcularán la pérdida correspondiente a un supuesto de perturbación futura aplicado a uno o varios factores de riesgo no modelizables utilizando los métodos de fijación de precios empleados en el modelo de medición del riesgo.

3.   No obstante lo dispuesto en el apartado 2, cuando, en relación con algunos instrumentos financieros o materias primas incluidos en la cartera a que se refiere el apartado 1, las entidades no puedan calcular la pérdida correspondiente a un supuesto de perturbación futura aplicado a uno o varios factores de riesgo no modelizables utilizando sus métodos de fijación de precios, realizarán las operaciones que a continuación se indican en el siguiente orden:

a)

identificarán dichos instrumentos financieros o materias primas y la causa de que el cálculo de precios falle;

b)

utilizarán métodos de fijación de precios basados en la sensibilidad, que incluyan al menos los términos significativos de primer orden y de segundo orden de las aproximaciones de la serie de Taylor, para reflejar la variación del precio de esos instrumentos financieros o materias primas debida a cambios en los factores de riesgo no modelizables en ese supuesto de perturbación futura.

4.   No obstante lo dispuesto en el apartado 2, y a efectos únicamente de determinar el período de tensión de conformidad con el artículo 12, apartado 1, las entidades podrán calcular la pérdida correspondiente a un supuesto de perturbación futura aplicado a uno o varios factores de riesgo no modelizables utilizando métodos de fijación de precios basados en la sensibilidad. Las entidades demostrarán que las variaciones de precios que no queden reflejadas en los métodos de fijación de precios basados en la sensibilidad no modificarían el período de tensión por ellas identificado.

CAPÍTULO 2
SUPUESTO EXTREMO REGLAMENTARIO DE PERTURBACIÓN FUTURA
Artículo 14

Determinación del supuesto extremo reglamentario de perturbación futura

1.   El supuesto extremo reglamentario de perturbación futura a que se refiere el artículo 325 ter duodecies, apartado 3, letra b), del Reglamento (UE) n.o 575/2013 corresponderá a una perturbación que dé lugar a la pérdida máxima que pueda producirse debido a un cambio en el factor de riesgo no modelizable cuando dicha pérdida máxima sea finita.

2.   Cuando la pérdida máxima a que se refiere el apartado 1 no sea finita, las entidades determinarán el supuesto extremo reglamentario de perturbación futura realizando las operaciones que a continuación se indican en el siguiente orden:

a)

valiéndose de un enfoque basado en expertos que utilice la información cualitativa y cuantitativa disponible, determinarán una pérdida debida a una variación del valor tomado por el factor de riesgo no modelizable que no vaya a superarse con un nivel de certeza igual al 99,95 % en un horizonte de diez días hábiles en un período futuro de tensión financiera equivalente al período de tensión identificado para el factor de riesgo no modelizable; al hacerlo, las entidades tendrán en cuenta la asimetría y el exceso de curtosis que puedan caracterizar los rendimientos del factor de riesgo no modelizable en un período de tensión financiera y justificarán cualquier hipótesis distributiva o estadística adoptada para identificar dicha pérdida;

b)

multiplicarán la pérdida obtenida de conformidad con la letra a) por

 

Imagen: data:image/jpg;base64,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

 

:

donde:

 

Imagen: data:image/jpg;base64,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 , y LH es el horizonte de liquidez del factor de riesgo no modelizable o los factores de riesgo del segmento estándar no modelizable a que se refiere el artículo 325 ter quinquies del Reglamento (UE) n.o 575/2013;

 

c)

considerarán que el supuesto extremo reglamentario de perturbación futura es la perturbación que da lugar a la pérdida resultante de las letras a) y b).

3.   Cuando las entidades calculen una medida del riesgo en un supuesto de tensión en relación con varios factores de riesgo no modelizables con arreglo al artículo 325 ter duodecies, apartado 3, letra c), del Reglamento (UE) n.o 575/2013, el supuesto extremo reglamentario de perturbación futura a que se refiere la letra b) de ese mismo apartado será un supuesto que dé lugar a la pérdida máxima que pueda producirse debido a una variación de los valores tomados por esos factores de riesgo no modelizables.

4.   No obstante lo dispuesto en el apartado 3, cuando las entidades calculen una medida del riesgo en un supuesto de tensión en relación con varios factores de riesgo no modelizables con arreglo al artículo 325 ter duodecies, apartado 3, letra c), del Reglamento (UE) n.o 575/2013 y la pérdida máxima a que se refiere el apartado 3 del presente artículo no sea finita, las entidades determinarán el supuesto extremo reglamentario de perturbación futura realizando las operaciones que a continuación se indican en el siguiente orden:

a)

valiéndose de un enfoque basado en expertos que utilice la información cualitativa y cuantitativa disponible, determinarán una pérdida debida a una variación de los valores tomados por los factores de riesgo no modelizables que no vaya a superarse con un nivel de certeza igual al 99,95 % en un horizonte de diez días hábiles en un período futuro de tensión financiera equivalente al período de tensión identificado para los factores de riesgo no modelizables; al hacerlo, las entidades tendrán en cuenta la asimetría y el exceso de curtosis que puedan caracterizar los rendimientos de los factores de riesgo no modelizables en un período de tensión financiera y justificarán cualquier hipótesis distributiva o estadística adoptada para identificar dicha pérdida;

b)

multiplicarán la pérdida obtenida de conformidad con la letra a) por

 

Imagen: data:image/jpg;base64,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

 

:

donde:

 

Imagen: data:image/jpg;base64,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 , y LH es el horizonte de liquidez de los factores de riesgo no modelizables a que se refiere el artículo 325 ter quinquies del Reglamento (UE) n.o 575/2013;

 

c)

considerarán que el supuesto extremo reglamentario de perturbación futura es el supuesto que da lugar a la pérdida resultante de las letras a) y b).

CAPÍTULO 3
CIRCUNSTANCIAS EN LAS QUE LAS ENTIDADES PODRÁN CALCULAR UNA MEDIDA DEL RIESGO EN UN SUPUESTO DE TENSIÓN PARA VARIOS FACTORES DE RIESGO NO MODELIZABLES
Artículo 15

Circunstancias en las que podrá calcularse una medida del riesgo en un supuesto de tensión para varios factores de riesgo no modelizables

Las circunstancias en las que las entidades podrán calcular una medida del riesgo en un supuesto de tensión para varios factores de riesgo no modelizables con arreglo al artículo 325 ter duodecies, apartado 3, letra c), del Reglamento (UE) n.o 575/2013 serán las siguientes:

a)

cuando los factores de riesgo pertenezcan al mismo segmento estándar a que se refiere el artículo 5, apartado 2, del Reglamento Delegado (UE) 2022/2060;

b)

cuando las entidades hayan evaluado la modelizabilidad de esos factores de riesgo determinando la modelizabilidad del segmento estándar al que pertenecen de conformidad con el artículo 4, apartado 1, del Reglamento Delegado (UE) 2022/2060.

CAPÍTULO 4
AGREGACIÓN DE LAS MEDIDAS DEL RIESGO EN UN SUPUESTO DE TENSIÓN
Artículo 16

Agregación de las medidas del riesgo en un supuesto de tensión

1.   A efectos de la agregación de las medidas del riesgo en un supuesto de tensión a que se refiere el artículo 325 ter duodecies, apartado 3, letra d), del Reglamento (UE) n.o 575/2013, las entidades determinarán, en relación con cada medida del riesgo en un supuesto de tensión que hayan calculado, la correspondiente medida del riesgo en un supuesto de tensión reajustada como sigue:

a)

cuando las entidades hayan determinado el supuesto extremo de perturbación futura para un único factor de riesgo de conformidad con el método por etapas establecido en el artículo 3, la correspondiente medida del riesgo en un supuesto de tensión reajustada se calculará con arreglo a la siguiente fórmula:

 

Imagen: data:image/jpg;base64,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

 

donde:

RSS es la medida del riesgo en un supuesto de tensión reajustada del factor de riesgo no modelizable;

SS es la medida del riesgo en un supuesto de tensión del factor de riesgo no modelizable;

 

Imagen: data:image/jpg;base64,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 , y LH es el horizonte de liquidez del factor de riesgo no modelizable a que se refiere el artículo 325 ter quinquies, apartado 1, del Reglamento (UE) n.o 575/2013;

 

κ es el coeficiente de no linealidad del factor de riesgo no modelizable calculado de conformidad con el artículo 17;

b)

cuando las entidades hayan determinado una medida del riesgo en un supuesto de tensión para varios factores de riesgo determinando un supuesto extremo de perturbación futura de conformidad con el método por etapas establecido en el artículo 6 para un segmento estándar no modelizable que comprenda esos factores de riesgo, la correspondiente medida del riesgo en un supuesto de tensión reajustada se calculará con arreglo a la siguiente fórmula:

 

Imagen: data:image/jpg;base64,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

 

donde:

RSS es la medida del riesgo en un supuesto de tensión reajustada del segmento estándar no modelizable;

SS es la medida del riesgo en un supuesto de tensión del segmento estándar no modelizable;

 

Imagen: data:image/jpg;base64,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 , y LH es el horizonte de liquidez de los factores de riesgo comprendidos en el segmento estándar no modelizable a que se refiere el artículo 325 ter quinquies, apartado 1, del Reglamento (UE) n.o 575/2013;

 

κ es el coeficiente de no linealidad del segmento estándar no modelizable calculado de conformidad con el artículo 18;

c)

cuando las entidades hayan determinado el supuesto extremo de perturbación futura para un único factor de riesgo de conformidad con el método directo establecido en el artículo 2, la correspondiente medida del riesgo en un supuesto de tensión reajustada se calculará con arreglo a la siguiente fórmula:

 

Imagen: data:image/jpg;base64,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

 

donde:

RSS es la medida del riesgo en un supuesto de tensión reajustada del factor de riesgo no modelizable;

SS es la medida del riesgo en un supuesto de tensión del factor de riesgo no modelizable;

 

Imagen: data:image/jpg;base64,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 , y LH es el horizonte de liquidez del factor de riesgo no modelizable a que se refiere el artículo 325 ter quinquies, apartado 1, del Reglamento (UE) n.o 575/2013;

 

UCF es el factor de compensación de la incertidumbre, que se calculará de conformidad con el artículo 20;

d)

cuando las entidades hayan determinado una medida del riesgo en un supuesto de tensión para varios factores de riesgo determinando un supuesto extremo de perturbación futura de conformidad con el método directo establecido en el artículo 5 para un segmento no modelizable que comprenda esos factores de riesgo, la correspondiente medida del riesgo en un supuesto de tensión reajustada se calculará con arreglo a la siguiente fórmula:

 

Imagen: data:image/jpg;base64,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

 

donde:

RSS es la medida del riesgo en un supuesto de tensión reajustada del segmento estándar no modelizable;

SS es la medida del riesgo en un supuesto de tensión del segmento estándar no modelizable;

 

Imagen: data:image/jpg;base64,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 , y LH es el horizonte de liquidez de los factores de riesgo comprendidos en el segmento no modelizable a que se refiere el artículo 325 ter quinquies, apartado 1, del Reglamento (UE) n.o 575/2013;

 

UCF es el factor de compensación de la incertidumbre, que se calculará de conformidad con el artículo 20;

e)

cuando las entidades hayan determinado una medida del riesgo en un supuesto de tensión determinando un supuesto extremo reglamentario de perturbación futura de conformidad con el artículo 14, la correspondiente medida del riesgo en un supuesto de tensión reajustada se calculará con arreglo a la siguiente fórmula:

 

Imagen: data:image/jpg;base64,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

 

donde:

RSS es la medida del riesgo en un supuesto de tensión reajustada;

SS es la medida del riesgo en un supuesto de tensión.

2.   Las entidades agregarán las medidas del riesgo en un supuesto de tensión con arreglo a la siguiente fórmula:

 

Imagen: data:image/jpg;base64,/9j/4AAQSkZJRgABAQABLAEsAAD/4gogSUNDX1BST0ZJTEUAAQEAAAoQAAAAAAIQAABtbnRyUkdCIFhZWiAAAAAAAAAAAAAAAABhY3NwQVBQTAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA9tYAAQAAAADTLQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAApkZXNjAAAA/AAAAHxjcHJ0AAABeAAAACh3dHB0AAABoAAAABRia3B0AAABtAAAABRyWFlaAAAByAAAABRnWFlaAAAB3AAAABRiWFlaAAAB8AAAABRyVFJDAAACBAAACAxnVFJDAAACBAAACAxiVFJDAAACBAAACAxkZXNjAAAAAAAAACJBcnRpZmV4IFNvZnR3YXJlIHNSR0IgSUNDIFByb2ZpbGUAAAAAAAAAAAAAACJBcnRpZmV4IFNvZnR3YXJlIHNSR0IgSUNDIFByb2ZpbGUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAdGV4dAAAAABDb3B5cmlnaHQgQXJ0aWZleCBTb2Z0d2FyZSAyMDExAFhZWiAAAAAAAADzUQABAAAAARbMWFlaIAAAAAAAAAAAAAAAAAAAAABYWVogAAAAAAAAb6IAADj1AAADkFhZWiAAAAAAAABimQAAt4UAABjaWFlaIAAAAAAAACSgAAAPhAAAts9jdXJ2AAAAAAAABAAAAAAFAAoADwAUABkAHgAjACgALQAyADcAOwBAAEUASgBPAFQAWQBeAGMAaABtAHIAdwB8AIEAhgCLAJAAlQCaAJ8ApACpAK4AsgC3ALwAwQDGAMsA0ADVANsA4ADlAOsA8AD2APsBAQEHAQ0BEwEZAR8BJQErATIBOAE+AUUBTAFSAVkBYAFnAW4BdQF8AYMBiwGSAZoBoQGpAbEBuQHBAckB0QHZAeEB6QHyAfoCAwIMAhQCHQImAi8COAJBAksCVAJdAmcCcQJ6AoQCjgKYAqICrAK2AsECywLVAuAC6wL1AwADCwMWAyEDLQM4A0MDTwNaA2YDcgN+A4oDlgOiA64DugPHA9MD4APsA/kEBgQTBCAELQQ7BEgEVQRjBHEEfgSMBJoEqAS2BMQE0wThBPAE/gUNBRwFKwU6BUkFWAVnBXcFhgWWBaYFtQXFBdUF5QX2BgYGFgYnBjcGSAZZBmoGewaMBp0GrwbABtEG4wb1BwcHGQcrBz0HTwdhB3QHhgeZB6wHvwfSB+UH+AgLCB8IMghGCFoIbgiCCJYIqgi+CNII5wj7CRAJJQk6CU8JZAl5CY8JpAm6Cc8J5Qn7ChEKJwo9ClQKagqBCpgKrgrFCtwK8wsLCyILOQtRC2kLgAuYC7ALyAvhC/kMEgwqDEMMXAx1DI4MpwzADNkM8w0NDSYNQA1aDXQNjg2pDcMN3g34DhMOLg5JDmQOfw6bDrYO0g7uDwkPJQ9BD14Peg+WD7MPzw/sEAkQJhBDEGEQfhCbELkQ1xD1ERMRMRFPEW0RjBGqEckR6BIHEiYSRRJkEoQSoxLDEuMTAxMjE0MTYxODE6QTxRPlFAYUJxRJFGoUixStFM4U8BUSFTQVVhV4FZsVvRXgFgMWJhZJFmwWjxayFtYW+hcdF0EXZReJF64X0hf3GBsYQBhlGIoYrxjVGPoZIBlFGWsZkRm3Gd0aBBoqGlEadxqeGsUa7BsUGzsbYxuKG7Ib2hwCHCocUhx7HKMczBz1HR4dRx1wHZkdwx3sHhYeQB5qHpQevh7pHxMfPh9pH5Qfvx/qIBUgQSBsIJggxCDwIRwhSCF1IaEhziH7IiciVSKCIq8i3SMKIzgjZiOUI8Ij8CQfJE0kfCSrJNolCSU4JWgllyXHJfcmJyZXJocmtyboJxgnSSd6J6sn3CgNKD8ocSiiKNQpBik4KWspnSnQKgIqNSpoKpsqzysCKzYraSudK9EsBSw5LG4soizXLQwtQS12Last4S4WLkwugi63Lu4vJC9aL5Evxy/+MDUwbDCkMNsxEjFKMYIxujHyMioyYzKbMtQzDTNGM38zuDPxNCs0ZTSeNNg1EzVNNYc1wjX9Njc2cjauNuk3JDdgN5w31zgUOFA4jDjIOQU5Qjl/Obw5+To2OnQ6sjrvOy07azuqO+g8JzxlPKQ84z0iPWE9oT3gPiA+YD6gPuA/IT9hP6I/4kAjQGRApkDnQSlBakGsQe5CMEJyQrVC90M6Q31DwEQDREdEikTORRJFVUWaRd5GIkZnRqtG8Ec1R3tHwEgFSEtIkUjXSR1JY0mpSfBKN0p9SsRLDEtTS5pL4kwqTHJMuk0CTUpNk03cTiVObk63TwBPSU+TT91QJ1BxULtRBlFQUZtR5lIxUnxSx1MTU19TqlP2VEJUj1TbVShVdVXCVg9WXFapVvdXRFeSV+BYL1h9WMtZGllpWbhaB1pWWqZa9VtFW5Vb5Vw1XIZc1l0nXXhdyV4aXmxevV8PX2Ffs2AFYFdgqmD8YU9homH1YklinGLwY0Njl2PrZEBklGTpZT1lkmXnZj1mkmboZz1nk2fpaD9olmjsaUNpmmnxakhqn2r3a09rp2v/bFdsr20IbWBtuW4SbmtuxG8eb3hv0XArcIZw4HE6cZVx8HJLcqZzAXNdc7h0FHRwdMx1KHWFdeF2Pnabdvh3VnezeBF4bnjMeSp5iXnnekZ6pXsEe2N7wnwhfIF84X1BfaF+AX5ifsJ/I3+Ef+WAR4CogQqBa4HNgjCCkoL0g1eDuoQdhICE44VHhauGDoZyhteHO4efiASIaYjOiTOJmYn+imSKyoswi5aL/IxjjMqNMY2Yjf+OZo7OjzaPnpAGkG6Q1pE/kaiSEZJ6kuOTTZO2lCCUipT0lV+VyZY0lp+XCpd1l+CYTJi4mSSZkJn8mmia1ZtCm6+cHJyJnPedZJ3SnkCerp8dn4uf+qBpoNihR6G2oiailqMGo3aj5qRWpMelOKWpphqmi6b9p26n4KhSqMSpN6mpqhyqj6sCq3Wr6axcrNCtRK24ri2uoa8Wr4uwALB1sOqxYLHWskuywrM4s660JbSctRO1irYBtnm28Ldot+C4WbjRuUq5wro7urW7LrunvCG8m70VvY++Cr6Evv+/er/1wHDA7MFnwePCX8Lbw1jD1MRRxM7FS8XIxkbGw8dBx7/IPci8yTrJuco4yrfLNsu2zDXMtc01zbXONs62zzfPuNA50LrRPNG+0j/SwdNE08bUSdTL1U7V0dZV1tjXXNfg2GTY6Nls2fHadtr724DcBdyK3RDdlt4c3qLfKd+v4DbgveFE4cziU+Lb42Pj6+Rz5PzlhOYN5pbnH+ep6DLovOlG6dDqW+rl63Dr++yG7RHtnO4o7rTvQO/M8Fjw5fFy8f/yjPMZ86f0NPTC9VD13vZt9vv3ivgZ+Kj5OPnH+lf65/t3/Af8mP0p/br+S/7c/23////bAEMAAwICAgICAwICAgMDAwMEBgQEBAQECAYGBQYJCAoKCQgJCQoMDwwKCw4LCQkNEQ0ODxAQERAKDBITEhATDxAQEP/AAAsIAG4DjQEBEQD/xAAdAAEAAgIDAQEAAAAAAAAAAAAABwgFBgEECQMC/8QAVRAAAQMDAwICBwUEBwQGBA8AAQIDBAAFBgcREgghEzEJFBgiQVHTVVaRlZcVIzJhFjhCcYGxtCQzUnQXcnaUssEZWWKHJig0NUNGY2R3goWSs+Hw/9oACAEBAAA/APVOlKUpSlKUpSlKUpSlKUpSlKUpSlKUpSlKUpSlKUpSlK1rUfUDHdLMJu2f5Y5JRabKx6xJMaOp93jySkBDaPeWolQAA+dRhO6tsatkZybcdINaI8ZkbuOq07uRSkb7bnignb/CsN7dek/3I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRp7dek33I1a/Tq7fRrI431n6Y5RkNrxqBh+qDMm7TGYLLkvArowwhbqwhKnHVtBLaAVAlaiAkbk9hU+UpSlKUpSlKUpSlKUpSlKUpSlKUpSlKUpSlKUpSlKUpSoP61v6sOef8ix/qmam1CU7HsPM/wCdc8R8z+JpxHzP4mgSk9wSf/zGnEfM/iacR8z+JpxHzP4mnEfM/iacR8z+JpxHzP4mnEfM/iacR8z+JpxHzP4mnEfM/iacR8z+JpxHzP4mnEfM/iacR8z+JpxHzP4mnEfM/iacR8z+JpxHzP4mnFPzPf8A9o04j5n8TQpAG/vfiaqpnPWvdLJZtQNR8H0tayjT/Su/O45k9wF/TFuKpTSWi+uJFU0UONNKeQlRW6hSjyKEkJ3NnMfvdryixW7JLNIU/b7rEZnRXdlJ5suoC0K2PcbpUDse9d/iPmfxNOI+Z/E04j5n8TTiPmfxNOI+Z/E04j5n8TTiPmfxNOI+Z/E04j5n8TTiPmfxNOI+Z/E04j5n8TTiPmfxNOI+Z/E04j5n8TTiPmfxNOI+Z/E04j5n8TTiPmfxNOI+Z/E04j5n8TTiPmfxNOI+Z/E04j5n8TTiPmfxNOI+Z/E04j5n8TTiPmfxNOI+Z/E04j5n8TTiPmfxNOI+Z/E04j5n8TXPEfz/ABNc0pSlKUpSlKUpSlKUpSlKUpSlKUpSlKUpSlKUpSlKUpSoP61v6sOef8ix/qmam5Hl/if86/VQ91Ra/Ren7TZV+gwUXfK73KbsuK2Tfddzur54st8QQooBIUsg7hI2Hcitn0RxbO8N0wsVi1OzN/KsrbYU/d7k5txXKdWpxxtrYD9y2VltvcA8EJ371vVKUpSlKUpSlKUpSoa6o4usMHA42oGiF2knIsJmpvblgCh6vkcJCSJNvd7EgqbJUhQ3IWgADdW43LRzVfFNb9M8f1TwqUXrRkEQSWeX8bSwSlxpf/tocStCv5pNbkfKqF9Wuq8jUe/X7Q06NavHTuGfWr9LxzCJy3MtntqCkQW5KWx4EPk2gPSQFLd7Jb2QCtV2cGTNRhdgTcsej2CWLXEEi1R3AtqA54KeUdCgAFJbO6AQACEis5SlKUpSlKUpSlKUpSlKUpSlKUpSlKUpXB7d6rFfNS+rHPNX8/w/QR7SeJj+CTINrfeyy23RyS9MehNyXQlcZ1KClPipHlv3HnX39V9JD9vdN/5Tfvr09V9JD9vdN/5Tfvr09V9JD9vdN/5Tfvr09V9JD9vdN/5Tfvr09V9JD9vdN/5Tfvr09V9JD9vdN/5Tfvr09V9JD9vdN/5Tfvr09V9JD9vdN/5Tfvr09V9JD9vdN/5Tfvr09V9JD9vdN/5Tfvr09V9JD9vdN/5Tfvr09V9JD9vdN/5Tfvr09V9JD9vdN/5Tfvr09V9JD9vdN/5Tfvr09V9JD9vdN/5Tfvr09V9JD9vdN/5Tfvr09V9JD9vdN/5Tfvr1wY3pIB537puH/wCk3369bppMz1fIyhStcLppBIx31VzinFYNzZm+s7p4Eqkuqb8PbnuNt9+O3xqZKUpSsdkN8gYzYblkV1e8GFa4j02Q5wKuDTSFLWrYdzslJOw71VbTnLfSI6l4BjeodqndPUGFk1qi3ePFmWi+eOw2+0lxKHNn9uYCgDt23B2rY/VfSQ/b3Tf+U3769PVfSQ/b3Tf+U3769PVfSQ/b3Tf+U3769PVfSQ/b3Tf+U3769PVfSQ/b3Tf+U3769PVfSQ/b3Tf+U3769PVfSQ/b3Tf+U3769PVfSQ/b3Tf+U3769PVfSQ/b3Tf+U3769PVfSQ/b3Tf+U3769PVfSQ/b3Tf+U3769PVfSQ/b3Tf+U3769PVfSQ/b3Tf+U3769PVfSQ/b3Tf+U3769PVfSQ/b3Tf+U3769cCN6R/fY3/pu/Kb79ep8wlOapxS1p1FesruSiOn9prsrbrcFT/fcspeJcCPLbkSazlKUqD+tb+rDnn/ACLH+qZqbkeX+J/zrmqU4qG+p70geRZNNcMvD+nSILPaWSjZpWRStxIeIV/Eprw3Edgdiy0rcduV1h27CuaUpSlKUpSlKUpSlcEbjaqU9P0lvpz61tR+mXm7GxHP4oz7DoygfCjvrJE6O15BCSoOEIG4CWB3BOxuvXG1c0pSlKUpSlKUpSlKUpSlKUpSlKUpSlKUrhX8Jqv/AEWyDken+X6oia5La1Dz7IMgjOmWmQgxUyfUowbWAP3YYhNAA/L5bAWBpSlKUpWuTtRMLtuc2zTWXkEZOT3iE/cYlrTyW+qKyQHH1BIIbbCiEhSykKV7qdyCK2OlKUpWsZ7qXgul8G3XTP8AJItjhXW5sWiNKlcgyZT3Lw0LWAUthXEjkspTvsCQSN9mB38qhXWHE9XM81Kx/GoeRXLGNK27RNmX67WG9Jt90cuIIEZnnx8VthKeThU2ocldl7ISUr1boK1O1C1T0hvd4zvIH8kjW3LrvacdyN9htpy+Whl0BiWoNpSgkkuI3CRv4fz3NWUpSlKhDrUySdjfTDn37IIN0vVt/o9bk+tCOoy7g4iG1xWewIL/AC/nxPceYlvF7DCxbG7VjNuU6qLaITEBguqClltltLaeRAAJ2SN+wrKUpSlK1zLNRMLwabYrblWQxoEzJrii02iMvkp6bKUNw22hIKjsBupW3FI7qIFbEDuNxXNKUrjy71rOJamYJnV3yKwYrksWfc8SuBtl6hp5IfhSNtwlaFgK4qHdKwChWx4qOx2zl3dubFqmPWWIzKuDcdxUVh90tNuvBJKEKWAopSVbAq2OwJOx8qotlN/6i9HrroHesh1Lv07VLUjMG7ZluFKnMy7U/blFxUhyKwlJTGRFbLXvtKBIVu4pagVVfNJ3ANc0pSoP61v6sOef8ix/qmam5Hl/if8AOtV1YzhjTTTHLNQ5LYW1jNlm3ZSSlRCvAZU5sQn3tt0jfbvtVafRY4jMtHS3Gzu9OiRedQ75cclnSCEcnFLdLKdyjz7MlWx7grUNgNquFSlKUpSlKUpSlKUpSqL+kgff0rzvQPqdtrAbXh2ZJtNzlNBRd/Z8tO7iCBxBSUNyE+8tIBcA/tmrysuNvNIdacStCwFJUk7hQPkQfj2r90pSlKUpSlKUpSlKUpSlKUpSlKUpSund7xacftsi8326RLdb4bZdkS5b6WWWUDzUtaiEpA+ZNYjCNR8A1LthvWnua2PJICVcVSLVPalNpVuRsS2o7HdKhsdvI1sdKVpWteYHT3R7N87S682rHsduN0SpkJLgUzGcWngFdirdI2B7b7ViOmbDJOnvT5p1hk6OWJdpxm3MSm1MBlSZHgJU7yQPJXiKVy+JO5Pc1JLxdDKywEFzieAWdk8tu2+3w3rzrwfr96lMh6iZnTNnOJaZ6f5UxIdgxXLs3dXo8+WlQDbTSkKHZ1BLjbitkrASBuVpFWm8HrTPf9paK/8Acbx9WsTfZPX3ASHMftOhF4SEKUtL0u8Ql8h5JSClwK3+ZUkA/jWgaW9WPUbbuoez6G9UOh9rw5jKorosF6s8h2XDlTUILgZ8bkpvcobdHHcLCkp3TxVvVxR371zWnawaoY3ovplkmqOWPhu2Y5b3ZrqQoBTykjZtlG/9txZQ2kf8SxUW9Hul93suFva06mJTM1N1R8O/X6Y43sqGw6kKi21nl7zbDDXAeGT/ABlZ+QFgt6b7+VNxQEEb05D/APwqILPrVkUnqXyLQq9Yxa4NttGKRsph3Zq5LddlMvSTHCXWlNoSwpK2ntwFOAjgdxuUiRMpxjFNRcVuWJ5PbIV6sd4jriTYjyUutPtnspJ/mPMEdwQCNiKgHo9zXKseuGYdKepEqRMyDSV5li03R8e/eMce5G3yFEAAuIbSGV7b90DclXI1neqrSTXTWe2W3D9OM1xOx4upaXr/AA7vClvqvKUr3EN0sLQRFUAPEQFBTgPEkI5JXt+geAah6f4xcompWV2m8XO4XIymY9lhLhWu1xkx2WG4sOOtSi00AyXCkHYuOuEedSdSlKVX7qpRIyPJtEdN4ciQ2b5qRAuk1CGEutvQrWw/PcQ4knfiXGWO48jsT5bKnG+uXtuxXBzG2Ibt2TEdMFuYtSGFSeB8MOKSCoIK+IUQCQN9q8+9EuvrqP1f1puegF7xfTTAM0t63mWoF8Yujipb7PIuso8NYAUlCSsb9lJ7p32q0fg9af2lor/3K8fVrB5FP9IFa0uPY9juhN9bbYLvBU+7wnnHBv8AukJUlaO+w2UpaRue+wG51PQbqu13uev7/T91O6MwMFu1ytr0/G5tuedfiXMse88hDxUtC/3ZKxxUCngQoAqSKtzXVudxg2e3Srtc5bUWHCZXIkPuqCUNNISVLWonsAEgkn5CqwdJkBeu+TXrrMzGMp5eQPyrPgESS3/8z46w8tpLqEKG7b8paVuOKB7o4AHie9qN6Ag+VCQKAg+VOQqIs81pyPDOobTDR1OKW5+y6isXZabubgsSYz0CKt9xv1bwuJSoKY2X4u/dwFA2BMb9YFvumjN1sfWPp9ZvHuWGEQM0hxmwHLzjDykh0LO26lxlhDzau3EBzc8dxVk4V4av+OM37GJMeW3cISZdvdcKktOpcb5NKOw5BJBST23APlvVTcc6ZOqxepMzPM31iwN+VfLxAlXK62yyTWrtEtcaQ28LVb3lvFEaKoIW2pHAlxLzpcK1K3q4g3271zSlKg/rW/qw55/yLH+qZqbkeX+J/wA6qz6TnJX8Z6K9QXI7S1quLcG2KKHi2UJfmMpUdx5jbcFPkQSD2qWumHGv6HdOmmeL82FqtuJ2phbjDfBDi/VWypYH8ySTv3JJJ7mpOpSuNxvtv3rmlK4/uqhXVv13a69Mmu8DT66YDh8LCL+qO7asquCLg+2iMopRIW8lg+84yrkpTTYKuBbP9sVPlsmdYl5t0W7Wq/aIS4U1lEiO+zEu6m3WlpCkLSQ7sUlJBB+INfm6e3THiF2zDQufJBGzMj9sxEkfE+IC53Hy49/mKhTU3qu62unu52u/61dPOHysAFybj3m/YpcJU31OLyHiP8FHm2AjkoFxtKSU8SUkirwxJTE6K1MiuBxl9CXG1p8lJUNwR/eCDX1puN9t6b7UCgfn+FNxWs6k5Hk2J4LeciwvEU5TfIUYuQLObg1BE57cBLXju+4jffzPy28zWYsMy4XGyW+fdrb+zpsmKy9Jh+KHfV3VIBW3zT2VxUSnkOx23qq3pU8fj3ronzaa/KcZNnk2ue2lG2zi/XWmglW/w2eJ7d9wKnXp3yxOdaDad5f6zEfdu2L2yU+qL2aD6oyPFSkbnYJWFp23O223wqQ6UpStW1N1JxXSPB7rqBmct1i12loOOBlouvPOKUEtstNjut1xakoQkealAfzrN2S4v3azwrpKtMu1uy2EPOQpnh+PGUpIJbc8NSkc077HipQ3B2Jrug79xXNKUpXBUkAqJGw86gFXWvpE1PtT8i25S1iV9vascteaqtYNhmXJMgxyyl8LLiU+KlaQ8ttLKvDXxWeJqSIereNvasTtGp0S4W7IGLW3e4RlNIEe6Qivw3HIziVHkWnPccQoJWnklXEoUFVu9KUqJOqTUPVfSjRy76haP4Xbsqu9jKZcq2zFPbrgpCvGW0lr3luJHFXHce6FnuQAa69KfVz1EdXGMXK+4PK0ftVwsr6WblZp0a7LkxUr5eC4VJcCVIcCF7FPkUkHuKnTwetT7S0V/wC5Xj6taVl+U+kdxuJIm2TS7RPKUtrWlpi33u4sSXUAKKV8JIQhJOwHHxCQVAbkbqrYujrqVyfqCxrJLdqXgi8Lz7C7sbZfrGpt1HghxPOO6kO+8ErSFjzO5bKh7qk1YStHy3V3G8Tz7E9MVw7jc8jzBUhcSHAaSv1WHHSC/NkqUpKWmEckJ3JKlrWlKEqO+27703BoSBQEHypyH/8AfwrS9QswzfGbriMHDtPhkrF7vTUG8Pm6swzaICh78zg57z/E8R4aO53r8I1dxtGri9F7lDuNuvztoF8trslpIiXWKlYQ/wCrupUd3GVlIcbWErAWlYCkbqGI1+0pxnVPG7MMyy+XYbJiV/g5ZNKHGUxJbcBfjeDM8ZJSY+6QtW+23AHftUG9NsJvJ+rjUzXK1Rm8ZxrOsfgpx+0yECLNySPFcQl2+riHZaGebgbbW4nktLwV7oUN7g0pVfut8xbrotE06kSWGl6h5ZjuIoDzC3UOJl3JjxkkI7j9w28rfcdknvvtU/NNpabS2gAJSNkgfAfAV+6o96TDo6XrVg41p01iOMajYNGMlHqgKX7pBaPiFkKBBDrXvutEbqJ5IA3UnbavR29Y0bqd0tTZMuuMdOouKoEe8MDZCp0cEBqchG/koFKXNvJ0HskLQKtvWu5xgGKai2qNZ8ttplx4VwiXaKpDzjLseZFeS6w8242QtC0rQO4I3G4O4JB2HyrmqiekWbk5XjOk+jLG7sfUXUuzWu5xmlAvOW9pSnn1BsnitCOCFK5BSRskkb7Vaq72WHebDMsDzkqPFmxXIqlwZTkV5ttaSndp1opW0oA+6tBCknYggivPbpLwa6ap69dSWnGbawavTrRp/kDNsx4o1DvDLsNlb01B3W2+PEVsy3sXAr+H47neTulrVbVS29VeqnSxkebXDUHFcLgRrha8kuCm3Z0Fa/C3hS320IDrh8VexUOQLCu57gax083fTTqtczyVrJqZkLGptlyq4xW7RHyeXZ3cXjsv+HGNuYQ8kJ7JTzeUhS1OFSF7pCQcbnGQa19LvSTmbuYZflCblI1Udt0/L3Gi7cE2GTKbSblHHZCXC0kJRuAgLUQBuUmto1b0KxjKdJmM86StS8quMyVLtUy4xrTl8u6NZPBE1rxlSEuvOEvhPJXjAoX7ikLOx2GodWeNam5t1L6gR9P2ZQtB0ph269x5NhuCY+QMx570qXZ49wbbKGHXYrm3NHNR58E7K5FFtumK66e3XR2yHTPTO5afWeMgsqxy4WR62PwJGwW6hTbqE+IeS9y8nklZJPInltDGpxawT0kGjt/tyng9qRh99xqe20AkFEICW04sncqG/biAnYoSdz3FW8rmlR7geo11yrUzUvCpsGIzEwq422HDda5eI8mTbWZSy5udtwt1SRxA7Ab96kKlKr1f0xcs65sUt8lEZ7/o+07ud4ZSphfiMyLpNZihYc/h7tQ3U7d+xX8xtYWvPn0nXSTcMjtrXVZo42/b89wsNy7qYAKX50RjiUSUqBB8aMEAjYbqbBH9hIqdOhXq2tPVZpExd50mIzmthS3DyWAzsni8QeElCNyQ08ElSfgFBaf7NWSrXcuwDFM5escnJLaqQ/jV2YvlqebfcZcjTGgpKVpU2oEgoWtCkHdK0LUlQIO1bD5dqrp6QvLZ+HdHmpE20SEN3C4wGbLGQXShbpmyWo60t8SCpfhuuEAeex3BG9SvpTgsDBdIMV07hsPRo1lsEO17J2ZeHCOlClEt7cXCeRJTt7xJFUd0fwy45L19azaE33VjVqbhuI2WHPtEFWod5QuO66iGtW7yJCXFgF9wALJ7Eb7kb1vukOouqelXXDcukp3P71qRhLuLC/syr1ITMumOuBIIbkyghC3EK2QkBzmo+OwrluV7/lvLtO9cerPVjRXqBze4QkYqIEXEsX/bcqzwpcVccPPTR4TzfrUrmtJBV/u0JQpsH3ynsC2azdNdl6mM8g5LkeYQbdi1oueC3TIJLlw/csxZhWwV7gvFhauSl91KSptS1KO+2Lw/TfT7XLpxa1J0L15zCVqvPxl4/wBIE5bJcnybmYxU7Cmw1OraQ34u48FLezQIU0fJRyE8XrHtVejVWSY7krbuK4pcm8hdNpmSk21+VZY8ZpEp5tC0oWp9txB5K3BBKtgdzbTUjELdqDp9kmDXcgQsgtMu2SCUcgG3mVNk8dxvty323G+3nUE+jdy+XmPRpp1KmqeW5bIkiypccUFc24klxhvbYD3QhCEgfAJHc+dWapWla25zcdMtHM51HtESNKnYtjlxvMZiTy8J12PHW6lK+JCuJKADsQdvKtugvqlQmJKwAp1pCyB5AlIP/nX3pUH9a39WHPP+RY/1TNTcjy/xP+dUZ9MXIlN9J9viMS3mWp2ZW2PIS2spDrfgylhKh/aHNCFbHtulJ8wKuliVijYvi1nxuG+68xaoEeC047tzWhppKApW2w3ISCdu29ZatS1H1Z040isicg1IzC3WKG6vwo/rLm7sp34NMMpBcfcO/ZDaVKPwFdLGs6yDUTFLzd8VxG644+EOtWKRlUAsImr4Hw5CoqXBJQzz2BS6GnFAEhIBBNf9B8810X1nahaR6q6mxclhY/hlrnx2bdaE22E2++4hSlIa5uLKvfUnkpwkjbsNgBbknYb1pmI6vYNmmZZVp9Z7otGRYbJQxdbdKZUw+hDiErbfQlXdxhYVsl1O6SQR5184WsmB3TVidovark9Oya02xN1ubUWMt1i3tLUEtNyHkjg064CVIaUQpSUlW222+8VDvVV01Yj1S6S3HTjJC3Em/wDyqzXXwvEcts1I2Q6kbjkkglC07+8hR8jsRSz0bHUplWlecXXoZ6g3RbLvj8p2HjTkpzyfS4S5bw4Ts4lQUHI5HulPJIJBbTXpoCCNxXXuVtgXi3ybTdIjUqHNZXHkMOp5IdaWkpWhQPYpIJBB8wax+GYjY8BxS04VjLDzFoscNqBBZdkuPqaYbSEto8RxSlqCUgAbknYAVSD0laMjwvIdJ8pwvUnUDH5GW5lDx+7xrTlk+JEkRFJSCEsNuhDa9gffbCSeSidzsR2essZp0Z4bZdbtFdYM0VJ/pBBtcvE8pyOVfIN6aWHSW2UzC68h7tufCcQOCVH+JKd9v6sdaGrHqRoVp/qNlN4wDAc+cnycjmRJrtvfTJZYbMaA/OaWkx2VOv8A70oIJ4JBKUcyMgxoPMwrXfR/J9EctyKXpixdruq+4+m+v3G2W99y0SRHlteItZabK1qQpvmUc3m1JSCSa0LR+/aY9UGf6s2rXPUS9Rs3xXMp1ttNgayaZZEWW3RVBuJLgMtPo5OkpWtyQQVhaikhKCnls9n0fyW0dOPUbhuvTszNGVX2+3K1XLI0h9U2A3aIqoMgFQCUqbU2E8kBIDrK1J79zY/Q9Sl6M4GtZJUrGbUST8/U2qj/AK6m23ekHVpDraFpGLTFAKSFDkACD3+IIBB+BANdToClRpfRzpS5FktPoRj7TSlNrCgFocWlaSR8UqBBHmCCDVgqVwo7Df8AmBUedP8AqPdtWtJrHn98gRIc26eteKzE5eEnwpTzI48yT3S2Cdz5k1IlVX1PWNXOuTTnSiX4L1h0vsD2o89jxUrTIubrpiW8LRvulbBCn0n/AO0SdtiDW29X921vxXSTL840t1AseMQsZxW53WQp6xqnz35LLKlNoZWp5LTKdgTzU24QoJPEjcVtvTDkt9zLpz0yy3J7k9cbvecStU6dLe25vvuRkKWtWwA3KiSe1SdSuCQPOo61D6gdLtNb1HxK8312flU5suQsas0Vy43aSNtwRFYCloQfLxHODe/moV2Mkd1Zy/BLXJwFyBgd+nvsuTUZLb03NyDGPLmgNRZIaU/vw2/eqQAVeZ2IhzoD1Gz7VbRzKb1qvlS8kuUfNr3bFSX2G2m/V2lNhLaW0jihsbq2Rudgrbc1XXWHVXpazJdo6ctO8hx60aYab5REuEyz2F1L1yym6GSpxNstEfkAWfGfJckcxyUrgyFBJVVjOvq3ycc0ss3UJj7CDkWjWQQ8oiHn4apEMupZnRCvfdKHmXCFAb78Ejz2Isra7hFu1ti3SE809HlstvsuNOBaFoWkKSUqHZQII2I7GtX1P1bwfR22Wm+6g3RdstV2u8eyiephS48V98L8JchwDZhoqQEeKvZAUtAJHLevpqfqpg+j2FTs/wA9vKIFphJSOQSXHZDqjs2yy2n3nXVq2CUJ3JJ+W5Gx2q4N3a2RLqzHksImMNyEtSmFMvNhaQoJcbUApCxvsUkAg7g9xXaI3G1eS3VPpflXo6+pOy9U+hlvCMDyOWqPdbO0goix1ud34KgFdmnUpU60fJtxOwHuJB9PdKtUMO1m0/supWB3Vu4WW+xhIjupI5IPktpYH8LiFhSFp+CkkVtta63gGKM587qczbVN5HItKbI/LQ+4lL8NLxebQ40FeGsoWpZSsp5JDiwCAoithV5dqq10bI/6Tcu1c6l7qI7knLcofxuyKakesCPY7UfV2ktuAkJDj3jOqCexPFW5BG0H4ThlyunpGs90AuOrGrUnB7PhjV7g246h3lKmJS/USVeMmQHVJ/fu7JUoj3v5DbesMzzU7RHros3S5A1Dv+oeC5Ljbt5W3f5gn3PHHUh5QU5KKA4pk+EhCQ6pZPjJO++2/wBchzfBtVetPUDQXX3NZ1tsVhs9pTiONm8SLVbr0X2Q9Kkuqbdb9akIcWlDaN+KUtckpK0qIy9rxXVbp4yDXnPLLkWRZtj0DTmBdMEXfpj1yQ07GRcXFQC7vzf4uhK99y4W3mwVqI3rWNCsL096htA7RqNp7r/ljmsk2yq8bJlZZI/aES7KaUpcV+F4imUxUvb7Rw1w4DmjuedZu+4J6h0+9LkzUPGgjN8YyTBoXrFyaBuEKQ48wiW0HFErBVx2Wncg8QSN0gjd+vWxTI2iTes2ONtDJtIbrDzO1uKcLRW3HcCZccuAghDsdbiVJ78tkjbfYiTM603076mtLINiziNNn4vfmItyVFg3h+M3KbUgONpW5GWnxW/eSrbcpJSlWx2FdPSDpi0b0Lu1wv2nePT49xucZuE/KuF5mXJ0MIVzDbapTrhbSVbEhGwUUp334jaVa4J271iMUy/HM3tKr7il1auVvTMlwPWGgeCn40hcd9KSQOXF1pxG47EpOxI71C+txeyXqS0GwVpxpUWBMvmZz0pmFt1CYUIRo/7sfxpL08ee3+7Vt8an8DYAD4VzXBAI715hZzoPLxr0llkufSDmFvhXySlV9zy1FLy4NnZWsGR6yUK4qTKC+SYwIUlwpUOCSlSfT0b7d65pSqgdY4B6nek/t3/plcv9MzVvB/uh/wBX/wAq84ekzSTFdUOrbq2GUv5Mwm35gz4Js2S3K0b+JIn8vE9Tfa8X+Abc+XH3tttzvs/QFmuF6O3TqO0ivU6HbbLpVl8mQi73ENJmyLat6QnxJbqUBx8tlrfxV79nkgbDYVmYXS50p9fGGr1nyLBm7BmM2fOgXqXjVzW2+xNjPOsFLySnw1ubJbc5La5KBQdyk7nW9HNTxgOgl70q1uuNs1EwS06uK0obvV9WosO2VwJCHXVrSUueC6fDJ3CUcT74DYVWE6nui7TPpNxOR1R9Ml8vWC5hi06G7Ctibi7Jg3TxX2mTB8NYU6ouclbI5qCuSgQBsU+jURbjsZpx5PFakAqHcbEjuK+oG1VD6xGXLh1MdKtttgD1yGaTpZZaUA96o1GQt9zbffw0pCir4dvj5VbtHZCQfkK/VRNqxi3UlfsgjyNIdWMPxazNxEodjXXFXLlIdkc1FS/FEhtKUceACQnfcKJJ3AFdNMcF6wX9YtYo1p19wONc413s6brJdwZbjctxVojKaU2j1oeEEtFCCN1blJV232q2Wldn1QseMqh6t5nZsnvZlOLTNtVnVbWQwQnggtFxzdQIWSrl35AbdtzmMyzPGdPsanZhmN3ZtlotqErkynQopQFKCEjZIJJKlJSAASSoAedZnfsSPhUA6CBeSa+6/agJmJkR2b7acMjlE0vIQm229DziAjybIeuDvIA/xctwCDvP9cKAKSFeVeYWn2g83T/0l81PSJmcBGMQWRPz62lLy4FoadVxetqlJVxedWvd1lsH9yv+IbNKB9PRvt3rmlVA9KTt7MbX/a6xbf8Aeat6P4T/AI15z4JprjupXpR+oK2ZO7kDLEXH7XJbNov8+0uFfq9uHvOQ3WlrTsT7qiU+R23ANZ3pCu+J6D9WPUloe48luyWdEfLY12uzqXbimP4Da5SXpSwZEllHjIKStSuASondThJ3u9aU9LfXjlOdW/UHCbY9keEXKNbYl1tNxcZuD1qeiMS4kpSkAAtueO8lKVpWkBB2IJ2EbaWXW7dGb3UXpTZL+/qFp9pjj9tyO12+8vla7auUhZetzzqUcUhTY8TglJBTxIAKlisnrX6PnpWnaf3XqE0VvMnTa522zO5NZ79Yrs4i2NqbaU+3IKTz8Nojjv4JTsAOI33BtZ00ZhlOoPT/AKeZvmySL7e8bgTp6i0WvEeWykqXx+HLsrt297t22qSXCAjdRGw233+VVI9Gaw8NFMxuKEg2656kZHLtbyFBTL8Xxm0BbRSdvD5ocA27bpP99W6r5ShJMZ0Q1tIfKFeEp1JUgL27FQBBI323AI/vqmPUhgnWPE6f9TZuUa/4BPszWI3hy4Qo2COMOvxhEdLjTbplK8NSk7pCyDxJB2O1SNjeAdaTbtrk3DqI09kW9KmFvsNYA42txkcSpCV+t+6SncA7dt99qsYN/jXNQf1rf1Yc8/5Fj/VM1NyPL/E/51Rb0xv9Viy/9uLZ/p5dXnj/AO4b/wCqP8q0fWmxasZDg79u0azG343f1OpPrUyKHebGx5ttrKVpYcO6eLqmngnY/u1b9oX0nvOk2mOQtN6uYNkmG57LU3A/pVnstFz/AGq5xBDcW9BSmAlRI4sD1cqPkyFAgWgYeZkMokR3EONOJC0LQQUqSRuCCOxB+dVB0vIV6THWXid+OB2JKtu/E7tHY/I7VcKqZ9WKZup2sOO4P0yqVF14xlr1iVl0Z8NQsZtDoJUxdFeG4l9L5/3UQoUvl+9HFIPLc+h2fgVkwu6aXMY7OxrUvH5Zez223mT6zdZdzd7ruTkggGW0/wDxNvp93iQkBO21WZpXnR6VbRPDcmuWA5vhF+Nr1rm3SNaMft8Eueu3tsOAp4lB/cmOtXMSDslIJST/AAbXv0vh55btPMdgan3O3XHK49uYavEu3oUiO9KCQFrQFd9ifj23O5ASCEjaKVQn0r0Bu52zQ23vh/wZWpERhwsuLaWErRxPFaCFIVsTspJBB7ggisB1f4Hg3TFrPoBrJYje5zS8vFkuTOUX2VeojcV0pJeSu4reMZ1G6lJcQpO3Hl5jerBa2ZN096w6vWXpO1dsOO5FHusK4S/DlSFokxLtGRDcajtFHFTbjkSa46FJWFcUbDfkdoOidN1g6JOp3SB3p9zK+M2nU28SrDkGH3CYqWiVFRGW8qY0kJBAY4pKlqJKSUd+JcB29XTb0pdeluvuoOYYLHtmaWvIrtj16l4/cVsy23YUp2O14/u8HFrYbYd3W2SAsJCiB31jpr6fLdqbbM+0V1I1AybLcf0fym64hj16iXV5hcm1TobPrtskrSOLwQni0sbcmypYQpKSmr32a0W/H7RCsVpj+BBt0dqJGa5FXBptAQhO6iSdkpA3JJ7VC/XN/VD1b/7Kzf8AwitJ9F42trod05S42pBP7WUApJG4N0lEHv8AAjvv8atXSoGy/BusO45Nc52Ja84BaLI9KWq3wZGDOyXY8fl+7Q46ZY8Re23JQABO+wA2AhLpawXrAn6FY1Kw/XzA7XaV+u+rxJWDLkut7TXwrk4JSeW6wojsNgQPhubq45HvkTHrXEye5RrheGYTDdwmRo5jsyJIQA6420VKLaVLCiEclcQQNztvVUcCbWj0nepiltqSHNMrSpJKSAoestDcfPuCN/5EfCpb6yVoR0n6vla0pBwm8JBUdhuYrgA/vJIAHxNfvo8Ch0o6Pggg/wBB7L5j/wC5t198rwDqCumQzrhivUBa7HaX3eUW3u4QzMVHRsPdLypKSvvudykedd7AMK1usN/E/PdbLdlFr8FaDAYxFq3K8Q7cV+Ml9Z2Hf3ePffz7VrfURiGu2RyrXK07yaccVipBvWPWGe1aL3cFBe4Me4upWhKeOwLP+zlWx/2hO+1fPQfMdA7Ptg2K4svTvKJAEmXjuRRDCvUpazsXluOqUq4EnYF5Drw32BVv2qcl/wAI2HxH+dVA9GL4buhuYEcXG3NRshII95Kklxr4+RBq1MfD8UiOtvxcatTLjKkrbW3BaSUKHcEEJ7EbdtqhD0g+/saaq7fYR/8A52qk/QxtbOiuAsuNqbWjF7SlSFJKSkiG1uCD3B/lXX14y7SrDNKr/ddaPUncTdjKiTYclkP+v+KOKYrbPm844TxSgdyT8NtxR/SXHMp0UzvBM56srBf2dMUFcXTRq9XYT2tPX3nlerM3dPhp2eW0W22pK1OCPsGiUkBSPR5C0OISttQUlQ3BB3BFfqtQ1cwfAdR9NshwvVBiM7i1zguIunrD/gNtsp98ul3ceGUFIWF7jiUg/CqPeih0+1Kwt3UR6y52xkWibl0eiY1LfjPsuXKWy4ErnRWlnZllSCUObg81oTxI8NW/ohSlVE9Fm04z0k2tp1pTa0ZBfEqQpJSUkTVggg+W1RKxp7YdSPSzalWTJHL61EZ0+iSkqtF7m2p7mlFuSN3obrThT753QVcSdiRuBtnOmX+jGhnX9rhoXA8RVrn2WLlcK5XqQJVy5lqMuQx646DIkNfvioJUtfHwCTurko73kWF9KnXpm+ZYfnOLWm63TCm7S7ZbzbZzrE+VZ7hbY81iUlxATyaK5DqQhXNA4hRAKwKjfSlm7dEuoWvOlWE5DcM209wrTo6hW+1XWQXFWieA7tblvJRsjxm2yvbj3QEKA5BZVl9Q/R+9IurOBu696TzndPZs20KyG3ZDj9zcYt8dYa8ZMhTRCktoTseYb8MpAV2ChW39LujVh13040y6ltXRf5eaTotov8tpy4vNQ5VxtyH48G4qj+QcLDhX7hS2su8ig7ipM65B/wDFD1bAH/1Unf8AgrbOmptbPTlpWy42ptaMJsaVIUkpKSIDO4IPcH+VSRStV1Rg5vdMDu1p05mRIWQXBtEOLNkrKUwkuuJbdkjYHktppTjqEHstaEpJAJIq36L6Wix6W6gaNPXVU2VppqHerGpbksurca8UKS6EEAoStYe27e8oOHz3FSbjbLmWdbWZ35xMgRMDwS02CMhxpstmXcZT0yQ4hf8AGD4TERJB7Hv/AI2BpUC9TfUFcNPDadItLGGrtq7noVGxm3KRzZhI3KXLlMOxCIzIClHcErKOIBAURsXTloRa9BsHXan7urIMrvcly65TkslsCVeri4oqW64e5CE8ihtG+yUAfEqJlfkn/iH41GesGu2OaT3HFMVLKbtlub3ePabDYm3vDek8nEh+QohKi2ww0VuLcKdvdCfNQqTAdxvXNVL9I5bnLbpngmr4acdjaW6iWHKJzaFBJVETI8FzdWxUB+9RvxB7dyNgdrQ3S12PMMdl2a7w2LjaLzEXGkx3U8m5Ed1BCkqHxSpKttvkajvD+lTp0wDI4mX4Xo5i1mvUFwusTocENvIWUlJVyB7nZSh3+Zr6Xvpf0KyHUCXqjdMCZVktxVDXPlMzpTDc8xHUOxzJYbcSzI4LaaUPEQrfw077gCsKnov6bWFqdtWnz9medDokvWW/XK2OzPEcU4oyXI0htUg81qILpUUg7DYdq2e4dOuiF0wCz6VztM7G5iFhlsz4FkDHGG2+2VFKlNAgOd1rKgvkFFRKgTWFx7pI6fsYvFqvdswR112xPiVao8+8z58K3PD+FyNEkPrYYUjchBQ2koHZOwqX65qoubwndS/SQ6eW+EUriaRYTcr/ADXWwUluXclGK0y4ogpPJsBaUDidgo7kDardUpWm4jpvFxPOs5zhm6vyXc3mwZj0dbaUoimNCaihKCO6goNBR38iSPKtyqmvpQ8O1FzHp2vblgvrFnxrGIKsjuS0SFJkzpceQwI0biE9mglb7xVvv4rTA7Dc1ZvSPL4uoOleI5xCWgs36yQbiAl8PBJdYQpSfEH8RBJST23IPlUX9D7EiboPH1Anwnos3US+XnMn0PtNodKZ051bBX4fuqPq4Y2Py2HkAKn+q69S2uuRwr9bOm3QmYy5q7mjBdjSXGvEi43bQT41zlnYgAJStLSTuVOFPY9kqkPQbRLFdA9P4uFY88udKWtU28XiSket3i4uHk/MkK3JU4tRPmTsNkg7CpG5J/4h+NRtqHrnjWDZ9helUVCLtmGbTw1FtLT/AAcj29sKXKnu7JVwabbQvjyA8ReyAR7ykySO43qBuu7Ap+pPSPqbi9rQ6uZ+xjco6WkpUta4biJQQkH4qDBT279ztudhW86IZXZtU9DcMy2K2hyDkWOQpC2VLLgT4kdIcaUrYcilXJJOw32NYCxdIXTNjF+g5Rj+iWJwLvbZDUuLNYgBLzTzagpCwvffcKSkj+4V3s96YtDdTcsezrMsEbl32VbDZZc1ifKiKmQCd1RpAYdQl9s7AFLgUCAEnt2rqZD0m9P2TZFOzG46fpYyG5TFTpV5t1zm2+4OOFlDJT6zGebdDXBtA8EKDe43477mspa+nLRazae37S23YJFaxvKC6u9xzIfW9c1u7eI5IkqWX3nFbDda3Crb41rbvRd00OrdbOmTaLc/JTLdsjV1nN2Vx0KCgVWxL4hkckpUQWtiociN+9TUyyzHZRHjtIbabSEIQhICUpA2AAHYAD4VqOsWcxdMtKsu1BmvsNNY9ZJtx5PpKkcmmVKSClJBVuoJGw7nfYdzUTej607naZ9IunljujTrM2db13qQ04e7Sprq5IRtxBTslxAKSNwdxudt6sVStX1SwWPqhpplem8y4OwGMqss2zOymkBa2EyGVNFaUnsSAvcA9u1bFEjiLFajBRUGm0oBPx2AH/lX1PaqoWnq4u9z642dDlMeHgt1sdwgWWYWU7XG/wAB4maW3PMtthD8cp8vEYUR/OQOtb+rDnn/ACLH+qZqbkeX+J/zqjvph4E+V0mRZ8OG4+zasvtkuWpO2zTRbkNBSv5Fx1tPbfusVcrC78nKcQseTJimMLtbYs4MlfMtB1pK+PLYb7ctt9hvtWarp3a0Wq/W2TZ73bItwgTW1MyYsplLrL7ZGxQtCgUqSR5ggitSwLRXTnTKzXTGcJsblusN2UpTtn9cedgslQUHBHYcWpMdCgru20Eo7AhIO5OpW3o26XLRc496tehWIRZ8V1D7Ulq3hLqVoUFJVy333BSD3+QqZdhttt2rEWLEMXxiXdp+PWCBbpN+mquNzejMJQuZKKUoLrpHda+KEjc/AAV+XMLxJ7Lmc+dxu2qySPAXa2rsYyPW0RFrDimA7ty8MrSFcd9t/wC81mqj/XLW7Bun7T2dqLn0x1uFHUmPGixm/Ekz5a9/CisI/turIOw7AAFRICSRF3TXo5m03KLj1NdQio8nUbKIyGbVa+ALWH2glSkW9gn/AOlUF7vrA3KgRufeKrIck/8AEPxrVNUtUsH0ZwW66jaiX1i02Kzsl199w91HyS22nzW4o7JShPdRIArtaeZLdMywWw5besccsE2826PPetbr3iuQy6gL8JauKd1pCgFe6NjuPhWpZ50yaA6n5C5leoOkmNZBd3UIbXMuEIOulKE8Ujc/IAAV2Mp6ddE800xj6NZLp1a5eGQ1odi2pIW03GWhalJW0ptSVtqBWv3kqB2WoeSiDg7n0f8AThfIrcW/6YQ7uWVznUSLlMlS5KXpimVSH/HddU74xMZgJe5eI2GwlCkp7VmsD6ddINN8mXmeMYvIVf1RTCTdbrd5t1ltRyrkWmnpjzq2kEncpQUgnz3rAyOjrp0duT96h6fuWi5S35UmXPst6uFrlTHJD6n3TIeivtuPjxFKUkOKUEb7JCQAKkTANO8J0sxeJhenuNQrFZYXIsxIiOKQpR3UtRO6lrUSSpaiVKPck1sdQD173OBaejvViXcpSI7K8cfipWvfYuvKQ00jt8VOLSkfzUK56CiT0e6T7kn/AODcf/xLqfaVwRuNv5g1puj2msXSHTu06ewrq/cmbV4/GU+2ltbniyHHjulPYbF0j+4VudVg6g4yNIOovTnqklrU3ja4L+n+YyQlxQhQ5ThdgS18TxS03L9xa1DZIfB/mJo1K0V0n1lat7eqOAWXJ27Z4phoucYPJZ8Tjz4g9u/ho/8A2iudNdFtKtHm57WmGB2fGUXPwvW0W6P4SXvD5eHyA/4ea9v+sa3alK1fUHTHT7VawLxfUbELXkFsUrmlidHDnhODycbV/E0sfBaClQ+BroztGtPLzp8xpbk1jVkWNxuAbiXuU9cFFKFlbYW68pTjnDcBJWonZIBJ2rEYD00aCaWX5OTadaT43jt0Q240mVboQZWELACx27dwAD/dUm1WLrOSnVv+iXSXZHlOXLUK6Rp9/DYc/wBhxqE8HpchxSCAgOLbbYQFHZanCkeRIs0y2llpLSAQlIAAJ32A8u9Yy/4njOUu2p7JLBAua7HcEXa2mWwl31SahC0IkN8h7riUuLAUO45HavpkeN2DL7DOxjKLPDutpubC4syFLZS6y+0obKQtCuxBFdm22232e3RbRaoTMOFCZRGjR2UBDbLSEhKEJSOwSEgAAeQFdgkAbmqgajZFc+tTUa5aBaaZJIt+leHSxH1KvsdJT+2n+Xaxw3O26fcX6wsHYBSU9wQHLYWKyWXGLNCx7HrbEttstzCIsSJFbS0ywygbJQhCeyUgAAAV3+Sfn+FRtimueNZ1rBkulGHIbuqcLgtOZBdWH92YVwecIagABOzjvhodW4Qr93xQkgqUrhJJG42qsPTyw1ojrnqd083p91uJld3kai4at8OFEqHL4i4RW1qJTyjyEhRb3CuL4c2PIkb3bOjrpfs13jX+16G4jFuUR9ElmW1AAeQ4hQUlQVvvuCkEf3CsrqN006JasZQzmuc4SmZfmLa9ZxcY1wlQn3ILoUHI7io7rZdbUFrHFfIbLUBtua6GQdJXT1kuRSswuGm8Zi/zFsLcu9unSrfPSGYyIrbbciM62400GG0I8JCkoIG5SSSazFg6eNG8ZwnJNPbPhTLdlzFmQxkAdlyH5V0Q+2ptz1iW44qQ6ShSkhSnCUg7JIrVnOivpnUh2IzpmmJbX3EOv2aFd58W0vrTx7u29p9MVzfgnkFNEL297epphw4luiMwLfFZjRYzaWWWWUBDbaEjZKUpHZIAAAA7ACq29a7zmpGP4/0p43MeTf8AVW5MNTjHQsrt+PxXkP3CY4pJAQjihDACjs4p/gAdztZGDDj26ExAiN+GxHbS00jkTxQkAJG57nYAedfelcKG6SPmKpl02uO4T18dSmmzr0nwcgZs+YwA9ECA8lbQS+tLgGxQlyQGx8+Kj5hVSX0oITkN71m1Vdjs+LleotwiR30NONlcG1tM25lJCzsSFR31ck9iVn+4WDr8uBwtqDSglZB4kjcA/DcfGqQR+hfqjgakZHqzauuVyDk2UhDU6Y3gUZwpjoJLcZnxZCyywnfs2ggHYFXIjethPS51vDufSJXEf+7+B9Wutc+krrXu8F62yvSLXtDT6eK1RcJixnQN9/dcafStB7eaVA11Omf0dMzRXXNevWpGuc7U+/NwX40Ndyti23WH3dgX/GckuqUoN+IgDYABxR+Aq6lKwWd4ZYtRsLvuBZPGU/acit0i1zW0K4qLLzZQvirb3VbK3CvgQD8Kg3pMyvJMIhudLGrsh1OZ4FHLdonSCkIyPH0rUiJNjnfdam2whp5I7trCeX8dWPpSlKVqGq+qOJ6N4JctQMzlutW+3pSlLTDZdkSn1qCGY7Lae7jri1JQlI8yr4AEiLuk7S3LrFDynW3Vu1ohajarXFF4u0PcLVaITaA3BtgX/a8BoAKOw3Uo7/w1YClKUrUNYMY/pvpPmmGAvg3/AB642wFhsLdBejONgoSeylbq7A+Z2qnnT/rC7avRUSMqceUbxi2KXmwoQYSxxmtOOxojRQnYq/3kZJUPMkkncGrg6O4S1ptpRh+n7PhFOO2KDbCWuXBSmWEIURy97YqBPfv3rZrq1cZFslsWiYzEnOMOJjPvMF5tp0pIQtTYUkrSFbEp5J3AI3G+9UkxzoQ6psSyjJc1x/rvlxb7l0pMu8zzgUV16SpIIQjm4+ooaQDshpJCEjsEitn9lvrf/wDWI3L9PoH1a6V46ROtW+W9y2zfSL35pl0pKlQ8MjxHRsQRs6y+hae477KG47HcGuz0j+j5PTdqle9X8z1elaj5Hc7d+z40yfbVMvRQpSS4suOPuqWpSUJQD22TyHferh1+XEJcQpC0ghQ2II3BqqugKJfS1qZdOmXKBJawjIrlIu+mF2fcSWCl4eNLsy1bjg+26XHGkEEuNqWQdwUi1lKUpSqq9Rb8zqY1BgdJuHocfxmBMiXXVO6tg+FEgtqS/HtKV9gZEpSUlQB3bbSFEEKIFpY0ZiHHbixWW2WWUBttttISlCQNgkAdgAAABX1pSlKpF6RvBmtOtPNP+onTyxRYMzRjLo94UxFZQ00YEuQkSkcUgbc3i0Tt/wAaz5kES51ZX62ZT0gZTk1kkpkW672aFPhvJIIcYdfjrbUCCQQUqB7Gp/R5f4n/ADqtHpIsOczToy1IiMR5Dztsgs3lKGVJSdosht5alcvNKW0rUQO5Ce3et86RcuGddMWl+UGc1LemYrbkyXWm+CfWG2UtPJCdhtxcbWnt23T27VLtKUpSlKqX1B9HuuGtesdq1TsfVKMUi4urxMatCMQanNW10thLkgl1/g6+o8iHS2CgcQnbjuep7LfW/wD+sSuX6fQPq1wOlzrePl6RK4n/AN38D6tRs/6LLPs01Cx7Mdcuru/aiwLLcmJr9rutndUiS02sKWwCuYpLSVgcCUp/hJr0HbbQ0hLbaEpSkbBKRsAPkK/VKUpSlVC9Kvkzdi6MMrtJjpeeyOda7UyPFCVBfrbb26U7brOzBHEd9iT8KsPohjknDtGMCxGatC5Njxi1255aEKQlTjMRtCiEq7gEpPY9/nW7UpSldS62q2X22S7Le7dGn2+ewuNKiSmkusvsrSUrbWhQIUlSSQQRsQa/Nlstqxy0QrDY4DMG3W5hEWLGZTxbZaQkJQhI+CQAAB8hXdpSlKUpWHt2H4taMguuV2zH4Ea83wMJuVwbYSmRLSyni0lxz+JSUAkJBOw3Ow7msxSlKj7XbBNQdS9N7lhWm2p6sAut02ZcvjVt9cfZjkEOJZHit+G4obAOA7pG5SArZSaw4F0OdV2mGKwcIwLrxfstktySmPEjaewuKeSipSipTxUtSlEkqUSok7kms/7LnW9vt/6RK47/AP4fwPq1rWc9CvVxqNbv2TlXpD8ndhlJQtiHjCYKHAVJOyxGlN8+6Rty3277eZ3mvo36UbL0j6YycEhZAnIblcrk7crjeDBEVclSgEto4c1kJQhOw3Ue6lHtyqeqw9+w/FsolWmdkWPwLjJsU1Nxtj0hhK3IcpIKQ60o90K4qUncbbgkHcGsxSlKUrDwsPxa3ZLcsyg4/AYvt4ZYjz7ihhIkyGmQQ02tz+IoTyVsnfYFRO25rMUpSqN625HatCvSI4jqfcZbcW1ZhpneoU9TlwLLZdtqHJfJ4K93hwbaSkJ3PM77du89dF9hm4/0u6dtXORIfm3S0C/y3X5HjuLkXF1c51RX/a3XJV/P5knvWK6rM61B0/vGjM3C8uctcHItS7Ni17giGw6mdDlrKlfvFpK2lJDCkgoI3Dqt/JJEh4LrjphqXlWTYXhGSLul2w+Y5b702iBJQ1FktuFtbXjLbS0taVJIIQtR+Pl3qBLHm2uMnr0u+iEnWaY7h1uxVGbIgmw25K1ByclkQC8GvE8FKF/x7+Idhurz37OkOaamdYi8qze3al3nT7T21X2XYbBCx1mKm6XExSlLkyXJkNO+GFKJ4sIQnYfxKV2Na/mWf9U+iGEa0X7Osjn36NYJ2Pt2LIYmNIWGLK6Upnz24ieLb0phtS3HASGebaTslBKR9NMMsyLPtVMOd0B6urhqTp8/Cuq8ojzX7W/crRJchqEGStAYZeLRcUkeEpvZDiU8twtQToGneu2pl6vWsFl1L647Vhb+nOV3KwW1M+zWBlc6NGB4yHGnG0rWSobEN7A7EDY+VrelDVDPtZdA8U1F1OxA4zkl1YdMyB4DrCf3by20PJbd99CXUIS4ASdgsbEjY1LldSRabXLnxLpKtsV6ZA8T1WQ4ylTrHiDivgojdHIAA7EbgbGu3SlKUrqT7Ta7qYxuduiyzCkJlxi+ylzwXkghLiOQPFYBOyhsRue9dry8q5pSlK/KuySfl3ryz0sWiy4xnfR8xIWv1jqLgWhptu87KYsq5CZzyWuYKzxatroVyGylunzIIPqanbbceR71AOiec6g3fqZ1606yvLnbzZcQOOSLEwuGwx6k3PYlPuNbtJBcCeLaApZKuKBud9ycp1jZNn+CdPuWaiab5s9jd3xOA9eEuIt8aYmWlptX+zuJfQoJQpSkkqTsocRsdiQa64dqvrZqLjFoiaV9Vz+XakScFYzmTYI1gx9yAgpXGD9uccbQHGH1qfW20FkbFBK1Did971VzrXK2dZ2mekuP6wTrRi2oNvuF2kW42G2vOQRBYC/AQ8ttSyHFIVzKlKKeR4kdttOumr2qcPq2z7RTLuryNhGNWO0w7za5U602Jhxa5Skq9VC5Leyw2lWwPdZABUT5maOjjWbPNYcVyxzMlx7xDxrJpdksWWRYRix8ot7W3hz0IG7Z5eRU0fDJ/hA2IqwddS4Wm13ZLKLpbosxMZ9uSyJDKXA28g7ocTyB2Uk9wodwfKu3SlKUrqQLTa7UZJtluixDNkKlySwylvxn1ABTi+IHJZ2G6juTsO9dulKUpWp6saf2zVXTTJ9N7wP9kyS1SbY4r4t+K2UpWP5pUUqH8xVEdLM1ueQejJy/BclcdOSaZSJGG3ht3cKadi3BotI2IBAS0ttHfvug7/IejCPL/E/51g88xK259hN+we8thcG/22TbJALaV/u3mlNq91QKTsFb7Ht2qqfoscuukrp4naUZKy6xfdLcjuGMzWnDuUgOl1A/hG3ErcRt3/g3377C5VKUpSlYvKLq1Ysbut7flLjNwIT8lbyIbktTYQgq5Bhr946RtvwR7ytth3NaJ00Zdcs70QxjK7vqLbs7lz2pCnMgt1sXb483jJdQCmOtKVN8QkNkFI3KCfjUf6r6rZ3l3UbYulXTDJE4nIVj6sxybIfVUSJTdrS+I6YsFDiVNh9xaty6sENpG4SpXasLl+a6i9KOpensLK9Srxnem+o19Tizz2QR46rnZLo82TFW3IjNtB5l1aVJUhbRKNioL/snQcp1b1WtHWDlOiWU9WrGEYrFxpvJbfLn2ixsLS8/JCUwUuSW+LiUNk7E7uHjuSe5MvdHWs+e6uW3N4+VzIuR2fGMidtWO5pDhCNHyWEkH/aEpRuypSVJ4qWyfDJOwSkgirE0pSlKVSDr1gL1j126eOmaOhqTHueSuZde2VJCg3Ago2JX5KSlaDKQCFAKPbzCau8ny71zSlKUpSlKUpSlKUpSocsWok26dUeR6dt6oQH4NpxaPLViKsfkR5cd9T6N5wmrR4chpSVhvZtRAUdiN0KJ2bXfVq16FaQ5Vq1eLe9PjYzblzPVGlcVSHNwhtrlseIU4tCSrY8QSdjtUSYhp51H5zp5bNUbn1I3O05tdYSbrDtVstcJeNRkvJ8VqG5GcZ9YfQlLgQp0vpcO24KSkVCOq/WHq5kHR/j3UZgWYpwbI7ZfkYplVmFriTIqbh6wll9XOQlZSlAHiI4LI2d2USU7jfbPrtneNa+adadYbr1bNdbXmDspvIY8SBbi/j8VtI8Of41tAShsrJSoPJIPEBJST3uQCSASNq5pSlKUpSlKVQL0s+C5FkVh0jvWI+sm6uZY5iqEx4CZCim6xyzvuewPucEpPmpzzBAq+FltrNmtEK0RkpS1BjtxmwlAQAlCQkbJHYDYDsPKq+9a+kuoesuP6fY7gliemNWXN7fkl1kxr8m1SmIsUOBSYz38aX1eMeC0kcSjfcEiuz0tYPrLo29eNGclx+BK05sT8k4fkP7QY/aLkQuhSI8yO0gBbm63FePuFKA/eDkd6wVm0z1didd1412fwNhOHXHD28NbkftqOZIU3KQ+JZYHcNngU8ORX5HbuUj5aX4Nqx0k3HI8HwzSeXqJpzebzKv9mfstzhx7tanZSit6JIamvNNvtpUkcHkOctiApJO5Tl51o6o04vlOosCzR15ZfsiszsDCHcgS7AiWWK423JYckrT4aHZDJkLcU2gpBU0AFqSoq1uy6O3fKuoXEdY7R05K0mkYbFnuXyemZbEv5Mp6OWW4CEwnVocZCgHC/IDagEtpSkclFGtaTdKmYXNrqBtGr+k+MMDVS93a/wBjuEp+JdPUVSkqS004ngFoW2sodCkEjcHYpIBVKPR2z1B4zgVk0v1k09ctDOG2Fi1/tqVeI81y7Sm33EJLAZWohhMZDBCnQhwqVx2PHkbE0pSlKUpSlKUpXB7javPbHNMrwz6XTJbg2Hk2VVgj5s8g29IbXI9QVbWtlnvsFPyFc0+awoEbjcehNV90nwTU7GeqfWTUK/YcxHxjPm7IxbJzd1ZdcSLZGdZKnWQApIdLu6QCSAPe237bH1a4bmmo/T9mWnOAWBq63nKba7aWUvTm4jTAdGxeWte+6U7fwpBJOw7DdQhZnSzWjB9KsftmkOgdltep8PA04U7kz+RxYsWIpbUYOyQ2yFGSrxY4cSpaEqBSPgpSazOc6SawyerPSDVGx4Q1cMX04scyyzpb1/aEmWqXHLSnW0ObrUGyQSXFBS/e+QKutYdB83uvWfnmrWoGkViuODZXY4lhiqnTYc1xoxggF5yMtJ2Q4ErGyVFQBG47kJ7PSXhXUFobcLholf8ATxp3CWMpvl0gZKm6RvUmLQ9+8hxIkVC/GbX46llTa0BCEleyj2FWwpSlKUpSlKUpSuCNxsfjXmR1GxV6Ia768YICmLj+tuIQ8ttiCCEG6w5TSZLaDvsVKT47pHmOSewHc+myPL/E/wCdcnv2qnEqErpm6805It5bGD9RcRFvkHiPDjZTEA8AKV/ZDzSlhI/tOOr/AOGrjggjcfGuaUpSlYHLc3xHB2rY7l+RQbQi83SNZoCpbwbEma+SGWEb+a1lJ2H8jUT9Ed3t+QdOFhv1plCTBud1yGZFeAIDrLl7nLQrY9xulQOx79+9YPV3R/UbGOoeydVmj9njZRcmrArEslxmTKRGemWovh9LsB5ZS2iShY34uqCHBsnkg7qrG5dptqv1Q6mYFd9QMCe090904vjeSotl1uEWZdL7c2kbR92ojjrEdholw8i8pauWwQkHcY1jQ7Pb11u5FrHmektmueC3fFmcVZVOnw5TqVtPIc9aVGWkgIUAtPEErAIJHcpH26WsD150HynINIJunLb2BTs3vV+tt/aucVFvttjkNKcjwosRK/GbdEoJ3QWw2EOOEK3ABthSlKUr5yH2YrDkiQ6hpppJWtazslKQNySfgAO9Uv6QosnqE6idS+tG4Nv/ANHXd8JwFt9JKVW2OpPjzGwoe6HVoBBHxcfSfKrqUpSlKUpSlKUpSlKUriq14jqbgOp3WBZ7tp/llvv8E6V3CQJMF3xWVIVfWWQUrHY/vIr6SB5Fs7+Y3lbXvSS267aPZVpLdbg/Aj5Lb1RBKZ25MuBSVtr2PmA4hBKfiAR233qJ8SyzqrwvT2HpY70+MXfKbPHTZoOTx7/DjY3JaabDbM10KdM5r3UpK2UsKPIEJVsoFMRan9Fuplk6O7D056eQIOX5HKyJvJ8jvUye1AYfmeP476tlhSl8iUtI90e4gKVsfdO9amaSaj4nrdpb1F6M6LxiLXa7ta8xxmxybdAmzG5DKfVg46pTbMhDTyUq25bjiCnffarS4pIyOXi9nlZhbotvvz0CO5dIkR4usR5ZbSXm21nutCVlQCviADWVpSlKUpSlKVhMqwrFM3Yt8bLLDEujVquUa7wkyUcgxMjq5MvJ+S0K7g1m6UpSlKUpSlKUpSlKUpSlKwYwjExmy9RhYIf9Jl2tNkVdOH+0GCl4vCPy/wCAOKK9vmazlKUpSlKUpSlKUpSlKUpVIPSoaSf0r00wzVWA3xm4HlEH1p1JAJt0x9pl1J8iQHfVz8dhy7bbkXdR5f4n/Ov1UbdQeheJ9RWl9y00y0ux0SVIlQLgwE+sW2c2d2ZLJI91aSSDttulS07gKNZLRZOqbWmVii60t2kZnFjmNdXbXIU9GkuNqKEvpUpKSC4hKXCnb3VKI+FbvSlKUrF5Hi2M5jbFWTLsdtl7ty1pcVEuMRuSypaTulRQ4CncHuDt2Ndq12q2WS3x7TZrdFgQYiA0xGispaaaQPJKUJACQPkBXapSlKUpSlRF1L4PqfqlgrWl+nlxh2eDlMkW/Jry5JKJEGzqH+0iMjgrm86jdpJJSE8yrf5b/gmEY3pthtlwLELcmDZbBBZt8GOklXBltISndR7qUdtyo9ySSe5rPUpSlKUpSlKUpSlKUpWBx3AsGxCVMnYnhlissm4rLkx63W5mMuSokkqcU2kFZ3JO537k1nq4rmlKUpSlKUpSlKUpSlKUpSlKUpSlKUpSlKUpSlKUpSlKUpSlKUpSlKUr8OtNPtqaebStChspKgCCP5g1+6UpSlKUpSlKUpSlKUpSlKUpSlKUpSlKUpSlKUpSlKUpSlKUpSlKV//Z

 

donde:

ICSR representa el conjunto de factores de riesgo no modelizables o segmentos estándar no modelizables para los que las entidades hayan determinado una medida del riesgo en un supuesto de tensión que se haya clasificado como reflejo únicamente del riesgo de diferencial de crédito idiosincrático, de conformidad con el apartado 3;

k es un índice que designa los factores de riesgo no modelizables o los segmentos estándar no modelizables pertenecientes a ICSR;

EIR representa el conjunto de factores de riesgo no modelizables o segmentos estándar no modelizables para los que las entidades hayan determinado una medida del riesgo en un supuesto de tensión que se haya clasificado como reflejo únicamente del riesgo de renta variable idiosincrático, de conformidad con el apartado 4;

l es un índice que designa los factores de riesgo no modelizables o los segmentos estándar no modelizables pertenecientes a EIR;

OR representa un factor de riesgo no modelizable o un segmento estándar no modelizable para el que las entidades hayan determinado una medida del riesgo en un supuesto de tensión que no se haya clasificado ni como reflejo únicamente del riesgo de diferencial de crédito idiosincrático, de conformidad con el apartado 3, ni como reflejo únicamente del riesgo de renta variable idiosincrático, de conformidad con el apartado 4;

j es un índice que designa los factores de riesgo no modelizables o los segmentos estándar no modelizables pertenecientes a OR;

 

Imagen: data:image/jpg;base64,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 son, respectivamente, las medidas del riesgo en un supuesto de tensión reajustadas en relación con los factores de riesgo no modelizables o los segmentos estándar no modelizables k,l, j calculadas de conformidad con el apartado 1;

 

 

Imagen: data:image/jpg;base64,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 .

 

3.   Los factores de riesgo no modelizables que las entidades clasifiquen como reflejo únicamente del riesgo de diferencial de crédito idiosincrático deberán cumplir todas las condiciones siguientes:

a)

que la naturaleza del factor de riesgo sea tal que refleje únicamente el riesgo de diferencial de crédito idiosincrático;

b)

que el valor tomado por el factor de riesgo no venga determinado por componentes de riesgo sistemático;

c)

que la correlación entre factores de riesgo sea insignificante;

d)

que las entidades realicen pruebas estadísticas para verificar la condición establecida en la letra c) y las documenten.

4.   Los factores de riesgo no modelizables que las entidades clasifiquen como reflejo únicamente del riesgo de renta variable idiosincrático deberán cumplir todas las condiciones siguientes:

a)

que la naturaleza del factor de riesgo sea tal que refleje únicamente el riesgo de renta variable idiosincrático;

b)

que el valor tomado por el factor de riesgo no venga determinado por componentes de riesgo sistemático;

c)

que la correlación entre factores de riesgo sea insignificante;

d)

que las entidades realicen pruebas estadísticas para verificar la condición establecida en la letra c) y las documenten.

Artículo 17

Coeficiente de no linealidad en relación con un único factor de riesgo

Cuando la medida del riesgo en un supuesto de tensión con respecto a la cual las entidades estén determinando el coeficiente de no linealidad se haya determinado para un único factor de riesgo, dicho coeficiente se determinará como sigue:

a)

cuando el supuesto extremo de perturbación futura aplicable al factor de riesgo no modelizable no coincida ni con la perturbación calibrada a la baja ni con la perturbación calibrada al alza determinadas de conformidad con el artículo 3, apartado 1, letra b), las entidades considerarán

 

Imagen: data:image/jpg;base64,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

 

para ese factor de riesgo no modelizable;

b)

cuando el supuesto extremo de perturbación futura aplicable al factor de riesgo no modelizable coincida con la perturbación calibrada a la baja determinada de conformidad con el artículo 3, apartado 1, letra b), las entidades calcularán el coeficiente de no linealidad con arreglo a la fórmula siguiente:

 

Imagen: data:image/jpg;base64,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

 

donde:

 

Imagen: data:image/jpg;base64,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 ;

 

 

Imagen: data:image/jpg;base64,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 ;

 

ɸ es la estimación del parámetro de cola para el factor de riesgo no modelizable calculada de conformidad con el artículo 19;

loss0 es la pérdida que se produce cuando la perturbación a la baja CSdown determinada de conformidad con el artículo 3, apartado 1, letra b), se aplica al factor de riesgo no modelizable;

 

Imagen: data:image/jpg;base64,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 es la pérdida que se produce cuando se aplica una perturbación a la baja igual a Imagen: data:image/jpg;base64,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 al factor de riesgo no modelizable, siendo CS down la perturbación a la baja determinada de conformidad con el artículo 3, apartado 1, letra b);

 

 

Imagen: data:image/jpg;base64,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 es la pérdida que se produce cuando se aplica una perturbación a la baja igual a Imagen: data:image/jpg;base64,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 al factor de riesgo no modelizable, siendo CS down la perturbación a la baja determinada de conformidad con el artículo 3, apartado 1, letra b);

 

c)

cuando el supuesto extremo de perturbación futura aplicable al factor de riesgo no modelizable coincida con la perturbación calibrada al alza determinada de conformidad con el artículo 3, apartado 1, letra b), las entidades calcularán el coeficiente de no linealidad con arreglo a la fórmula siguiente:

 

Imagen: data:image/jpg;base64,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

 

donde:

 

Imagen: data:image/jpg;base64,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 ;

 

 

Imagen: data:image/jpg;base64,/9j/4AAQSkZJRgABAQABLAEsAAD/4gogSUNDX1BST0ZJTEUAAQEAAAoQAAAAAAIQAABtbnRyUkdCIFhZWiAAAAAAAAAAAAAAAABhY3NwQVBQTAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA9tYAAQAAAADTLQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAApkZXNjAAAA/AAAAHxjcHJ0AAABeAAAACh3dHB0AAABoAAAABRia3B0AAABtAAAABRyWFlaAAAByAAAABRnWFlaAAAB3AAAABRiWFlaAAAB8AAAABRyVFJDAAACBAAACAxnVFJDAAACBAAACAxiVFJDAAACBAAACAxkZXNjAAAAAAAAACJBcnRpZmV4IFNvZnR3YXJlIHNSR0IgSUNDIFByb2ZpbGUAAAAAAAAAAAAAACJBcnRpZmV4IFNvZnR3YXJlIHNSR0IgSUNDIFByb2ZpbGUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAdGV4dAAAAABDb3B5cmlnaHQgQXJ0aWZleCBTb2Z0d2FyZSAyMDExAFhZWiAAAAAAAADzUQABAAAAARbMWFlaIAAAAAAAAAAAAAAAAAAAAABYWVogAAAAAAAAb6IAADj1AAADkFhZWiAAAAAAAABimQAAt4UAABjaWFlaIAAAAAAAACSgAAAPhAAAts9jdXJ2AAAAAAAABAAAAAAFAAoADwAUABkAHgAjACgALQAyADcAOwBAAEUASgBPAFQAWQBeAGMAaABtAHIAdwB8AIEAhgCLAJAAlQCaAJ8ApACpAK4AsgC3ALwAwQDGAMsA0ADVANsA4ADlAOsA8AD2APsBAQEHAQ0BEwEZAR8BJQErATIBOAE+AUUBTAFSAVkBYAFnAW4BdQF8AYMBiwGSAZoBoQGpAbEBuQHBAckB0QHZAeEB6QHyAfoCAwIMAhQCHQImAi8COAJBAksCVAJdAmcCcQJ6AoQCjgKYAqICrAK2AsECywLVAuAC6wL1AwADCwMWAyEDLQM4A0MDTwNaA2YDcgN+A4oDlgOiA64DugPHA9MD4APsA/kEBgQTBCAELQQ7BEgEVQRjBHEEfgSMBJoEqAS2BMQE0wThBPAE/gUNBRwFKwU6BUkFWAVnBXcFhgWWBaYFtQXFBdUF5QX2BgYGFgYnBjcGSAZZBmoGewaMBp0GrwbABtEG4wb1BwcHGQcrBz0HTwdhB3QHhgeZB6wHvwfSB+UH+AgLCB8IMghGCFoIbgiCCJYIqgi+CNII5wj7CRAJJQk6CU8JZAl5CY8JpAm6Cc8J5Qn7ChEKJwo9ClQKagqBCpgKrgrFCtwK8wsLCyILOQtRC2kLgAuYC7ALyAvhC/kMEgwqDEMMXAx1DI4MpwzADNkM8w0NDSYNQA1aDXQNjg2pDcMN3g34DhMOLg5JDmQOfw6bDrYO0g7uDwkPJQ9BD14Peg+WD7MPzw/sEAkQJhBDEGEQfhCbELkQ1xD1ERMRMRFPEW0RjBGqEckR6BIHEiYSRRJkEoQSoxLDEuMTAxMjE0MTYxODE6QTxRPlFAYUJxRJFGoUixStFM4U8BUSFTQVVhV4FZsVvRXgFgMWJhZJFmwWjxayFtYW+hcdF0EXZReJF64X0hf3GBsYQBhlGIoYrxjVGPoZIBlFGWsZkRm3Gd0aBBoqGlEadxqeGsUa7BsUGzsbYxuKG7Ib2hwCHCocUhx7HKMczBz1HR4dRx1wHZkdwx3sHhYeQB5qHpQevh7pHxMfPh9pH5Qfvx/qIBUgQSBsIJggxCDwIRwhSCF1IaEhziH7IiciVSKCIq8i3SMKIzgjZiOUI8Ij8CQfJE0kfCSrJNolCSU4JWgllyXHJfcmJyZXJocmtyboJxgnSSd6J6sn3CgNKD8ocSiiKNQpBik4KWspnSnQKgIqNSpoKpsqzysCKzYraSudK9EsBSw5LG4soizXLQwtQS12Last4S4WLkwugi63Lu4vJC9aL5Evxy/+MDUwbDCkMNsxEjFKMYIxujHyMioyYzKbMtQzDTNGM38zuDPxNCs0ZTSeNNg1EzVNNYc1wjX9Njc2cjauNuk3JDdgN5w31zgUOFA4jDjIOQU5Qjl/Obw5+To2OnQ6sjrvOy07azuqO+g8JzxlPKQ84z0iPWE9oT3gPiA+YD6gPuA/IT9hP6I/4kAjQGRApkDnQSlBakGsQe5CMEJyQrVC90M6Q31DwEQDREdEikTORRJFVUWaRd5GIkZnRqtG8Ec1R3tHwEgFSEtIkUjXSR1JY0mpSfBKN0p9SsRLDEtTS5pL4kwqTHJMuk0CTUpNk03cTiVObk63TwBPSU+TT91QJ1BxULtRBlFQUZtR5lIxUnxSx1MTU19TqlP2VEJUj1TbVShVdVXCVg9WXFapVvdXRFeSV+BYL1h9WMtZGllpWbhaB1pWWqZa9VtFW5Vb5Vw1XIZc1l0nXXhdyV4aXmxevV8PX2Ffs2AFYFdgqmD8YU9homH1YklinGLwY0Njl2PrZEBklGTpZT1lkmXnZj1mkmboZz1nk2fpaD9olmjsaUNpmmnxakhqn2r3a09rp2v/bFdsr20IbWBtuW4SbmtuxG8eb3hv0XArcIZw4HE6cZVx8HJLcqZzAXNdc7h0FHRwdMx1KHWFdeF2Pnabdvh3VnezeBF4bnjMeSp5iXnnekZ6pXsEe2N7wnwhfIF84X1BfaF+AX5ifsJ/I3+Ef+WAR4CogQqBa4HNgjCCkoL0g1eDuoQdhICE44VHhauGDoZyhteHO4efiASIaYjOiTOJmYn+imSKyoswi5aL/IxjjMqNMY2Yjf+OZo7OjzaPnpAGkG6Q1pE/kaiSEZJ6kuOTTZO2lCCUipT0lV+VyZY0lp+XCpd1l+CYTJi4mSSZkJn8mmia1ZtCm6+cHJyJnPedZJ3SnkCerp8dn4uf+qBpoNihR6G2oiailqMGo3aj5qRWpMelOKWpphqmi6b9p26n4KhSqMSpN6mpqhyqj6sCq3Wr6axcrNCtRK24ri2uoa8Wr4uwALB1sOqxYLHWskuywrM4s660JbSctRO1irYBtnm28Ldot+C4WbjRuUq5wro7urW7LrunvCG8m70VvY++Cr6Evv+/er/1wHDA7MFnwePCX8Lbw1jD1MRRxM7FS8XIxkbGw8dBx7/IPci8yTrJuco4yrfLNsu2zDXMtc01zbXONs62zzfPuNA50LrRPNG+0j/SwdNE08bUSdTL1U7V0dZV1tjXXNfg2GTY6Nls2fHadtr724DcBdyK3RDdlt4c3qLfKd+v4DbgveFE4cziU+Lb42Pj6+Rz5PzlhOYN5pbnH+ep6DLovOlG6dDqW+rl63Dr++yG7RHtnO4o7rTvQO/M8Fjw5fFy8f/yjPMZ86f0NPTC9VD13vZt9vv3ivgZ+Kj5OPnH+lf65/t3/Af8mP0p/br+S/7c/23////bAEMAAwICAgICAwICAgMDAwMEBgQEBAQECAYGBQYJCAoKCQgJCQoMDwwKCw4LCQkNEQ0ODxAQERAKDBITEhATDxAQEP/AAAsIACAAagEBEQD/xAAdAAADAAICAwAAAAAAAAAAAAAABgcFCAEEAgMJ/8QAMBAAAAUEAQMDAgQHAAAAAAAAAQIDBAUGBxESAAgTIRQiMRVBFhgjMlFXWJaX0dP/2gAIAQEAAD8A+qfDhw4cOHDhw4pXUujRll6Ekbk3Ck1I6n4k7cr10RuouKILLpoFMJEwEwlA6pciADgMj9uI9purywV9aoPSVoa0Wqh6g2O7dqM4p4VuzTKIAXvLKJFIQTiOCBnJtTYDwPLLw4jXlQvM5oZw3sO8pNpVh10QRXqYq5mSaO36oiVEBMJ9fBft5881aqbrjuhO0bQ9tbS0HDyN/qucPY+Shjr92Pp4WDxVo8eudTbAgZRuqKQGMA6e4dsFKfdGF+sBDsQqE7M8oDZIHxmZTFbi40DuCmBxEwE221AwiOMZHPO5w4c55N7x3BujQaUUe2li5W45nplgeFYzbGO9CBAJoJhdGLvvsbGucaDn5Dkz/MN1T/0IVV/e8H/15S7OXCulXhZYbl2JlbbixFD0QPptjI+v337mvpTm001JnfGe4GPgeY3qppKr63spJQFCUy3qGb+sQD5vFuXBEEXRWswzcqkUUUyUpO2ifYRA3tAcFMOCjO6XvPO2avfTdibx0dQkSvclFw4puYo5BVs1UctwDdm7RWDYD4N7FgMIHEwF0KI55Urc1JfOYuVX8XcW38PB0ZFuW6VISTV+C7iWREphVUWKBx7ePZgokJgTGD342Gm8nd/Ze8sLayYd2CpJhUVbnKRCMavnibdFMxzAUy5hUECn7YCJ9BMXbGM/YdSIXpFvV00NKHvFaWloe6F2TSEy7uGLl8nHnmzyaYGEyThUQAibdZMmCgAbic59S7CAUU9QdRdTdXSFplrtPKTgHVtmFZy8UxjY54pHPzujNVGrJ2q2ETJ7pCJlFinEQMfUC5KJJlbS+fUo8s5Ya9VU3dPIL3FuTF0o+iU4JiizPFKuHSCh1BBLu+qMKAHE6ZyEL7QAn7hN6L5dU1+KTnr01jbarJaoKctxPw8c19FERqULFrd1NJ9HyBnOHjoxjqAGzTIpm19xQMIA9dX99br2LnWlx7f3KWqSm5pnKRy9GIxzf1EUsgiZI0uiuRoqp2Gy5NlwXyQBHACICBA2MsPF1ewtzGPK1vEe5b+VQRf/AFsjJm2anKdIg4alapkKKAjkxRPscdvJvgALw2XjryNIxnJV5XdNpxiiqofhaol4ky5jgUP1jJeVAKBR1ARwGxv48mP5G6U/nzfz/JUh/vlJs5Y6JswEsEXXlfVJ9X7Hc/FVSuJbsdrfHZ7w/pbdwdtf3akz+0OJ3WHZ6r7u0RTA0Um5evqPqxhUqkQ2mDxSsu3RKoRRoR2UQ7JxBXYphEA2IACJc7AoSNq7q9QPUVbu69fUVJW9pK1QOnzGKkJVm7fS8ouUpSnErNRVJFFMCh7hUE5xAS6AA7ccLfXBvmXqhre1NxY6mFaS+jp1BSzqJFT1Ldp6grcqbwDeAOqPdMXOMigrpsUB1vPDhxAlrC2gnKyeXDlKCi16lkGhmDqVEpwcqthT7YomOBgHtiUADX4++M+eYQvSf06khI+miWip4sVEvDSDBkVAwINHRsZWSIBsJn8Z2Lgc5H5EeeUr0qdPk5KSctLWvinSk0AjJt1DLCzfKCAB312u/YVX8Bhc5BUDzg3kedqmemawlHLSTimrU06wVl4laBfKJNfc4jlcdxqYRERFI2pck+PHGW3drrfWlgz0zbako6nYo65nIs2CXbRBUwABjAXOAEdQzjjTw4cOccwcLQ9LU9UU/VkRElRl6nVQWlXYqnUO4FBIEki+8wgQhCB4ITUoCY5sbHMI53n/2Q==

 

ɸ es la estimación del parámetro de cola para el factor de riesgo no modelizable calculada de conformidad con el artículo 19;

loss0 es la pérdida que se produce cuando la perturbación al alza CSup determinada de conformidad con el artículo 3, apartado 1, letra b), se aplica al factor de riesgo no modelizable;

 

Imagen: data:image/jpg;base64,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 es la pérdida que se produce cuando se aplica una perturbación al alza igual a Imagen: data:image/jpg;base64,/9j/4AAQSkZJRgABAQABLAEsAAD/4gogSUNDX1BST0ZJTEUAAQEAAAoQAAAAAAIQAABtbnRyUkdCIFhZWiAAAAAAAAAAAAAAAABhY3NwQVBQTAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA9tYAAQAAAADTLQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAApkZXNjAAAA/AAAAHxjcHJ0AAABeAAAACh3dHB0AAABoAAAABRia3B0AAABtAAAABRyWFlaAAAByAAAABRnWFlaAAAB3AAAABRiWFlaAAAB8AAAABRyVFJDAAACBAAACAxnVFJDAAACBAAACAxiVFJDAAACBAAACAxkZXNjAAAAAAAAACJBcnRpZmV4IFNvZnR3YXJlIHNSR0IgSUNDIFByb2ZpbGUAAAAAAAAAAAAAACJBcnRpZmV4IFNvZnR3YXJlIHNSR0IgSUNDIFByb2ZpbGUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAdGV4dAAAAABDb3B5cmlnaHQgQXJ0aWZleCBTb2Z0d2FyZSAyMDExAFhZWiAAAAAAAADzUQABAAAAARbMWFlaIAAAAAAAAAAAAAAAAAAAAABYWVogAAAAAAAAb6IAADj1AAADkFhZWiAAAAAAAABimQAAt4UAABjaWFlaIAAAAAAAACSgAAAPhAAAts9jdXJ2AAAAAAAABAAAAAAFAAoADwAUABkAHgAjACgALQAyADcAOwBAAEUASgBPAFQAWQBeAGMAaABtAHIAdwB8AIEAhgCLAJAAlQCaAJ8ApACpAK4AsgC3ALwAwQDGAMsA0ADVANsA4ADlAOsA8AD2APsBAQEHAQ0BEwEZAR8BJQErATIBOAE+AUUBTAFSAVkBYAFnAW4BdQF8AYMBiwGSAZoBoQGpAbEBuQHBAckB0QHZAeEB6QHyAfoCAwIMAhQCHQImAi8COAJBAksCVAJdAmcCcQJ6AoQCjgKYAqICrAK2AsECywLVAuAC6wL1AwADCwMWAyEDLQM4A0MDTwNaA2YDcgN+A4oDlgOiA64DugPHA9MD4APsA/kEBgQTBCAELQQ7BEgEVQRjBHEEfgSMBJoEqAS2BMQE0wThBPAE/gUNBRwFKwU6BUkFWAVnBXcFhgWWBaYFtQXFBdUF5QX2BgYGFgYnBjcGSAZZBmoGewaMBp0GrwbABtEG4wb1BwcHGQcrBz0HTwdhB3QHhgeZB6wHvwfSB+UH+AgLCB8IMghGCFoIbgiCCJYIqgi+CNII5wj7CRAJJQk6CU8JZAl5CY8JpAm6Cc8J5Qn7ChEKJwo9ClQKagqBCpgKrgrFCtwK8wsLCyILOQtRC2kLgAuYC7ALyAvhC/kMEgwqDEMMXAx1DI4MpwzADNkM8w0NDSYNQA1aDXQNjg2pDcMN3g34DhMOLg5JDmQOfw6bDrYO0g7uDwkPJQ9BD14Peg+WD7MPzw/sEAkQJhBDEGEQfhCbELkQ1xD1ERMRMRFPEW0RjBGqEckR6BIHEiYSRRJkEoQSoxLDEuMTAxMjE0MTYxODE6QTxRPlFAYUJxRJFGoUixStFM4U8BUSFTQVVhV4FZsVvRXgFgMWJhZJFmwWjxayFtYW+hcdF0EXZReJF64X0hf3GBsYQBhlGIoYrxjVGPoZIBlFGWsZkRm3Gd0aBBoqGlEadxqeGsUa7BsUGzsbYxuKG7Ib2hwCHCocUhx7HKMczBz1HR4dRx1wHZkdwx3sHhYeQB5qHpQevh7pHxMfPh9pH5Qfvx/qIBUgQSBsIJggxCDwIRwhSCF1IaEhziH7IiciVSKCIq8i3SMKIzgjZiOUI8Ij8CQfJE0kfCSrJNolCSU4JWgllyXHJfcmJyZXJocmtyboJxgnSSd6J6sn3CgNKD8ocSiiKNQpBik4KWspnSnQKgIqNSpoKpsqzysCKzYraSudK9EsBSw5LG4soizXLQwtQS12Last4S4WLkwugi63Lu4vJC9aL5Evxy/+MDUwbDCkMNsxEjFKMYIxujHyMioyYzKbMtQzDTNGM38zuDPxNCs0ZTSeNNg1EzVNNYc1wjX9Njc2cjauNuk3JDdgN5w31zgUOFA4jDjIOQU5Qjl/Obw5+To2OnQ6sjrvOy07azuqO+g8JzxlPKQ84z0iPWE9oT3gPiA+YD6gPuA/IT9hP6I/4kAjQGRApkDnQSlBakGsQe5CMEJyQrVC90M6Q31DwEQDREdEikTORRJFVUWaRd5GIkZnRqtG8Ec1R3tHwEgFSEtIkUjXSR1JY0mpSfBKN0p9SsRLDEtTS5pL4kwqTHJMuk0CTUpNk03cTiVObk63TwBPSU+TT91QJ1BxULtRBlFQUZtR5lIxUnxSx1MTU19TqlP2VEJUj1TbVShVdVXCVg9WXFapVvdXRFeSV+BYL1h9WMtZGllpWbhaB1pWWqZa9VtFW5Vb5Vw1XIZc1l0nXXhdyV4aXmxevV8PX2Ffs2AFYFdgqmD8YU9homH1YklinGLwY0Njl2PrZEBklGTpZT1lkmXnZj1mkmboZz1nk2fpaD9olmjsaUNpmmnxakhqn2r3a09rp2v/bFdsr20IbWBtuW4SbmtuxG8eb3hv0XArcIZw4HE6cZVx8HJLcqZzAXNdc7h0FHRwdMx1KHWFdeF2Pnabdvh3VnezeBF4bnjMeSp5iXnnekZ6pXsEe2N7wnwhfIF84X1BfaF+AX5ifsJ/I3+Ef+WAR4CogQqBa4HNgjCCkoL0g1eDuoQdhICE44VHhauGDoZyhteHO4efiASIaYjOiTOJmYn+imSKyoswi5aL/IxjjMqNMY2Yjf+OZo7OjzaPnpAGkG6Q1pE/kaiSEZJ6kuOTTZO2lCCUipT0lV+VyZY0lp+XCpd1l+CYTJi4mSSZkJn8mmia1ZtCm6+cHJyJnPedZJ3SnkCerp8dn4uf+qBpoNihR6G2oiailqMGo3aj5qRWpMelOKWpphqmi6b9p26n4KhSqMSpN6mpqhyqj6sCq3Wr6axcrNCtRK24ri2uoa8Wr4uwALB1sOqxYLHWskuywrM4s660JbSctRO1irYBtnm28Ldot+C4WbjRuUq5wro7urW7LrunvCG8m70VvY++Cr6Evv+/er/1wHDA7MFnwePCX8Lbw1jD1MRRxM7FS8XIxkbGw8dBx7/IPci8yTrJuco4yrfLNsu2zDXMtc01zbXONs62zzfPuNA50LrRPNG+0j/SwdNE08bUSdTL1U7V0dZV1tjXXNfg2GTY6Nls2fHadtr724DcBdyK3RDdlt4c3qLfKd+v4DbgveFE4cziU+Lb42Pj6+Rz5PzlhOYN5pbnH+ep6DLovOlG6dDqW+rl63Dr++yG7RHtnO4o7rTvQO/M8Fjw5fFy8f/yjPMZ86f0NPTC9VD13vZt9vv3ivgZ+Kj5OPnH+lf65/t3/Af8mP0p/br+S/7c/23////bAEMAAwICAgICAwICAgMDAwMEBgQEBAQECAYGBQYJCAoKCQgJCQoMDwwKCw4LCQkNEQ0ODxAQERAKDBITEhATDxAQEP/AAAsIADwAaQEBEQD/xAAdAAEAAgMAAwEAAAAAAAAAAAAABggBBQcDBAkC/8QAMhAAAQQBBAIBAwAIBwAAAAAAAQIDBAUGAAcREgghExQiMQkVIzJBUWGBFhhSV5ax0//aAAgBAQAAPwD6p6h25W7eB7SRKWXnN0mAnILqHQVqAgrckTZLgbbQlI9kAnso/hKQSdTAHnWdNNNNNNNNNNeGXLiwIr06bIajx47anXXXVhKG0JHKlKUfQAAJJP4A183PK9N9ulZbNeQ96zYRqmy3jxymwWtdS60GqQrdWue60rj9vOcaadSFICm2GmE/lS9fShP4/udZ00000000001p8vxLHs8xe1wzLaxFjTXcR2DPiLWpKX2HE9VoJSQoAgkeiDqjHlR4Xy7iwwui2P2HuLCvx7JKu+sbCRuG+hqRCZ+UPQWWZUtSmnSC31eSE9R+6oe9XW2wrDTYDR1hxaXjhjREo/VUuzNi9E9n9muSVr+Uj/V3V+fzqUazpqE7u7y7ebHYmcx3Hvk10FyQiFEbQ0p6ROlrB+ONHZQCt51XU8ISCeAT6AJHL3PLt7G6oZtutsHuPgeCvBK28js48SQiK2QClybFivOSYiVFSEgqbVwpX39OCdbCH5c4XYbf7dZZWYvf2l7ulF+qxzFa8MO2UhAQXHFq7OIababQOy3VrCU8ge1EA+HGvLCNYbs4zsZmG02Y4hmmQic79LZNsORExozC3TJalsrU1IbUUhACD3So/clI9nvmmmmtff5DQ4rUSL/J7uBUVkQBUibPkojsMgqCQVuLISnlRA9n8kD+OoR/mR8ef999u/8AlMD/ANdTDF8vxPN6sXeG5PU31cXFNCXWTWpTPdPHZPdtSk8jkcjnkc6im+NBuve4QXNlcxjUGWVUxmyhpmsJdg2Qa5KoMr12Sy8D1K0ELQQlQPog8Ac8sNwt+GGdktjcRssS3VUFxs3fuoZXHwBCVdHHlKIDcx5w8mKlBKXBwtfVII1bHH62XT0VfUz7mXbyYcVqO9YSw2H5a0ICS64G0pQFqI7HqkDkngAapHua9J3A/SobbYPlQ+soMKw6TklTCU2CymxWHQX1hQIUpJQ0Un0UqbQQQR7vBa1UC6q5dNZx0Pw5zDkaQ0scpcaWkpWk/wBCCR/fVGNxPHne3bah2N3H8RMkpc8t9rKORQO1777LDF/UvFPKkH5ehAKOCPl/PRST2SQdrtD5MVm93kPhmL+Q+xGT7RbnYyiymYg3OdUuNaNSIhaltBxbKFE/H94QPtJaSe3ZISbvaaaa9Wyra63hO11tBjzIj/AcYkNJdbX7BAKVAg+wD7H8NVqR5LeAj0j6FjKtv3p5kmEmuapAucuR8nxfCmKGC8pwr+0JCST645BGrI1FLTUMT6CiqodfG7FfwxI6GUdj+T1QAOTx+dQvfGJvHaYQaLY+fUVeQW0xmE7c2XK01ENfb55jTPHD76EgfG2ohJUoFR4SQeM2/hVC25x6my7xsuF0e6mLJef/AF5auqf/AMWl1XySY10r8yEPr9hz95lXUt8AddWYx+RdS6KvlZHWx6+1eitOTYkeSZDUd8oBcbQ6Up+RKVcgK6p5A54GuAeT3jfl+e5thXkDsreQarc/bpaxCaslLTX3MBwn5oMlSAVICgpwJWPQ+RYP5C0e/YbmeT2ZUDeM41452OC5FYp+nfvb++q5lXTg+lyG0xX1vy1IH3NtlpoLPHZSBzqEWW0W8OxW5G2NpsRt6zmOK4Vt/Lxe5Zm27EKZOSZMdxAYU59v1Kltl7hQQyQFoK0co43ljiO6u++/e2ed5JtLI2+xba92wtg7dzYEm0sp8iP8CGGEw3XkMx0pPdxSnAVqCAEjoFHkOTb+7/UPipvfm8bd6S7lO1W6E7Ha+zXTVveZXsSosZDD7IYDXv6haypCEr7JAB68pPVs5vN6rrzJTsvjW+Nri+MWG37mWpYi0dXJejyGZzUQtMuSGFnqsKLiu/yHkqCeo46ynxI3RzvcCmz3G9w7+tyKz29zSfiqL+C0hkWzLSG3W3nG2wGm3QHui0t/aFIP9dd61+Vjkev5j/vVAsMeyDxQ2qq95t0fFfBotNjVo81c36XWDljDcmxdbTYhH0/VSSH20/EJHylKuf5gXxpLmryOmgZDRzWpldZxmpkOS0eUPMOIC21pP8QpKgQf6697TTTWNZ1jgfjXF8/8N/HDdC0ubbN9uUWDuQPNyrJpFpNjx5MlAATJUw08lr6gJHX5gn5OpUnt1UQedZd4fWWY+TFDn1tVY4rbrHsTXi1fGj39rDu4nZZeMpl5gJKFhZWx1D4BZdXyffTVjsEwHDNscWg4TgGNwKGjrUFEWDCaDbTfJKlHj8lRUSSo8kkkkk6kGtJm9HPybDL7HKq1crJtrWSoUea2VBUZ11lSEOjqQrlKlBXog+vRGqSy8P8AIzKPEmP4fja7Pms0tY7VNfZlk1xDn1TLKpIcly0Sy6t59pSOUtMhoOIS4E88t9jdTbzD4u3uA41gMGU7JjY1Tw6dl90ALdbjsoaStXHrkhAJ4/nqQ6aaaaaaaaaaaxwOeeBzrOmmmmmmmmmmmv/Z al factor de riesgo no modelizable, siendo CS up la perturbación al alza determinada de conformidad con el artículo 3, apartado 1, letra b);

 

 

Imagen: data:image/jpg;base64,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 es la pérdida que se produce cuando se aplica una perturbación al alza igual a Imagen: data:image/jpg;base64,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 al factor de riesgo no modelizable, siendo CS up la perturbación al alza determinada de conformidad con el artículo 3, apartado 1, letra b).

 

Artículo 18

Coeficiente de no linealidad en relación con un segmento

Cuando la medida del riesgo en un supuesto de tensión con respecto a la cual las entidades estén determinando el coeficiente de no linealidad se haya determinado para un segmento estándar no modelizable, dicho coeficiente se determinará como sigue:

a)

cuando el supuesto extremo de perturbación futura no corresponda a un supuesto determinado de conformidad con el artículo 6, apartado 1, letra b), en el que el valor del parámetro β a que se refiere el artículo 6, apartado 1, letra c), se fije en 1, las entidades considerarán el coeficiente de no linealidad

 

Imagen: data:image/jpg;base64,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

 

para ese segmento no modelizable;

b)

cuando el supuesto extremo de perturbación futura sea un supuesto en que la correspondiente perturbación a la baja determinada de conformidad con el artículo 6, apartado 1, letra b), se aplique a cada uno de los factores de riesgo del segmento no modelizable, las entidades calcularán el coeficiente de no linealidad con arreglo a la fórmula siguiente:

 

Imagen: data:image/jpg;base64,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

 

donde:

 

Imagen: data:image/jpg;base64,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 ;

 

 

Imagen: data:image/jpg;base64,/9j/4AAQSkZJRgABAQABLAEsAAD/4gogSUNDX1BST0ZJTEUAAQEAAAoQAAAAAAIQAABtbnRyUkdCIFhZWiAAAAAAAAAAAAAAAABhY3NwQVBQTAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA9tYAAQAAAADTLQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAApkZXNjAAAA/AAAAHxjcHJ0AAABeAAAACh3dHB0AAABoAAAABRia3B0AAABtAAAABRyWFlaAAAByAAAABRnWFlaAAAB3AAAABRiWFlaAAAB8AAAABRyVFJDAAACBAAACAxnVFJDAAACBAAACAxiVFJDAAACBAAACAxkZXNjAAAAAAAAACJBcnRpZmV4IFNvZnR3YXJlIHNSR0IgSUNDIFByb2ZpbGUAAAAAAAAAAAAAACJBcnRpZmV4IFNvZnR3YXJlIHNSR0IgSUNDIFByb2ZpbGUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAdGV4dAAAAABDb3B5cmlnaHQgQXJ0aWZleCBTb2Z0d2FyZSAyMDExAFhZWiAAAAAAAADzUQABAAAAARbMWFlaIAAAAAAAAAAAAAAAAAAAAABYWVogAAAAAAAAb6IAADj1AAADkFhZWiAAAAAAAABimQAAt4UAABjaWFlaIAAAAAAAACSgAAAPhAAAts9jdXJ2AAAAAAAABAAAAAAFAAoADwAUABkAHgAjACgALQAyADcAOwBAAEUASgBPAFQAWQBeAGMAaABtAHIAdwB8AIEAhgCLAJAAlQCaAJ8ApACpAK4AsgC3ALwAwQDGAMsA0ADVANsA4ADlAOsA8AD2APsBAQEHAQ0BEwEZAR8BJQErATIBOAE+AUUBTAFSAVkBYAFnAW4BdQF8AYMBiwGSAZoBoQGpAbEBuQHBAckB0QHZAeEB6QHyAfoCAwIMAhQCHQImAi8COAJBAksCVAJdAmcCcQJ6AoQCjgKYAqICrAK2AsECywLVAuAC6wL1AwADCwMWAyEDLQM4A0MDTwNaA2YDcgN+A4oDlgOiA64DugPHA9MD4APsA/kEBgQTBCAELQQ7BEgEVQRjBHEEfgSMBJoEqAS2BMQE0wThBPAE/gUNBRwFKwU6BUkFWAVnBXcFhgWWBaYFtQXFBdUF5QX2BgYGFgYnBjcGSAZZBmoGewaMBp0GrwbABtEG4wb1BwcHGQcrBz0HTwdhB3QHhgeZB6wHvwfSB+UH+AgLCB8IMghGCFoIbgiCCJYIqgi+CNII5wj7CRAJJQk6CU8JZAl5CY8JpAm6Cc8J5Qn7ChEKJwo9ClQKagqBCpgKrgrFCtwK8wsLCyILOQtRC2kLgAuYC7ALyAvhC/kMEgwqDEMMXAx1DI4MpwzADNkM8w0NDSYNQA1aDXQNjg2pDcMN3g34DhMOLg5JDmQOfw6bDrYO0g7uDwkPJQ9BD14Peg+WD7MPzw/sEAkQJhBDEGEQfhCbELkQ1xD1ERMRMRFPEW0RjBGqEckR6BIHEiYSRRJkEoQSoxLDEuMTAxMjE0MTYxODE6QTxRPlFAYUJxRJFGoUixStFM4U8BUSFTQVVhV4FZsVvRXgFgMWJhZJFmwWjxayFtYW+hcdF0EXZReJF64X0hf3GBsYQBhlGIoYrxjVGPoZIBlFGWsZkRm3Gd0aBBoqGlEadxqeGsUa7BsUGzsbYxuKG7Ib2hwCHCocUhx7HKMczBz1HR4dRx1wHZkdwx3sHhYeQB5qHpQevh7pHxMfPh9pH5Qfvx/qIBUgQSBsIJggxCDwIRwhSCF1IaEhziH7IiciVSKCIq8i3SMKIzgjZiOUI8Ij8CQfJE0kfCSrJNolCSU4JWgllyXHJfcmJyZXJocmtyboJxgnSSd6J6sn3CgNKD8ocSiiKNQpBik4KWspnSnQKgIqNSpoKpsqzysCKzYraSudK9EsBSw5LG4soizXLQwtQS12Last4S4WLkwugi63Lu4vJC9aL5Evxy/+MDUwbDCkMNsxEjFKMYIxujHyMioyYzKbMtQzDTNGM38zuDPxNCs0ZTSeNNg1EzVNNYc1wjX9Njc2cjauNuk3JDdgN5w31zgUOFA4jDjIOQU5Qjl/Obw5+To2OnQ6sjrvOy07azuqO+g8JzxlPKQ84z0iPWE9oT3gPiA+YD6gPuA/IT9hP6I/4kAjQGRApkDnQSlBakGsQe5CMEJyQrVC90M6Q31DwEQDREdEikTORRJFVUWaRd5GIkZnRqtG8Ec1R3tHwEgFSEtIkUjXSR1JY0mpSfBKN0p9SsRLDEtTS5pL4kwqTHJMuk0CTUpNk03cTiVObk63TwBPSU+TT91QJ1BxULtRBlFQUZtR5lIxUnxSx1MTU19TqlP2VEJUj1TbVShVdVXCVg9WXFapVvdXRFeSV+BYL1h9WMtZGllpWbhaB1pWWqZa9VtFW5Vb5Vw1XIZc1l0nXXhdyV4aXmxevV8PX2Ffs2AFYFdgqmD8YU9homH1YklinGLwY0Njl2PrZEBklGTpZT1lkmXnZj1mkmboZz1nk2fpaD9olmjsaUNpmmnxakhqn2r3a09rp2v/bFdsr20IbWBtuW4SbmtuxG8eb3hv0XArcIZw4HE6cZVx8HJLcqZzAXNdc7h0FHRwdMx1KHWFdeF2Pnabdvh3VnezeBF4bnjMeSp5iXnnekZ6pXsEe2N7wnwhfIF84X1BfaF+AX5ifsJ/I3+Ef+WAR4CogQqBa4HNgjCCkoL0g1eDuoQdhICE44VHhauGDoZyhteHO4efiASIaYjOiTOJmYn+imSKyoswi5aL/IxjjMqNMY2Yjf+OZo7OjzaPnpAGkG6Q1pE/kaiSEZJ6kuOTTZO2lCCUipT0lV+VyZY0lp+XCpd1l+CYTJi4mSSZkJn8mmia1ZtCm6+cHJyJnPedZJ3SnkCerp8dn4uf+qBpoNihR6G2oiailqMGo3aj5qRWpMelOKWpphqmi6b9p26n4KhSqMSpN6mpqhyqj6sCq3Wr6axcrNCtRK24ri2uoa8Wr4uwALB1sOqxYLHWskuywrM4s660JbSctRO1irYBtnm28Ldot+C4WbjRuUq5wro7urW7LrunvCG8m70VvY++Cr6Evv+/er/1wHDA7MFnwePCX8Lbw1jD1MRRxM7FS8XIxkbGw8dBx7/IPci8yTrJuco4yrfLNsu2zDXMtc01zbXONs62zzfPuNA50LrRPNG+0j/SwdNE08bUSdTL1U7V0dZV1tjXXNfg2GTY6Nls2fHadtr724DcBdyK3RDdlt4c3qLfKd+v4DbgveFE4cziU+Lb42Pj6+Rz5PzlhOYN5pbnH+ep6DLovOlG6dDqW+rl63Dr++yG7RHtnO4o7rTvQO/M8Fjw5fFy8f/yjPMZ86f0NPTC9VD13vZt9vv3ivgZ+Kj5OPnH+lf65/t3/Af8mP0p/br+S/7c/23////bAEMAAwICAgICAwICAgMDAwMEBgQEBAQECAYGBQYJCAoKCQgJCQoMDwwKCw4LCQkNEQ0ODxAQERAKDBITEhATDxAQEP/AAAsIACAAagEBEQD/xAAdAAADAAICAwAAAAAAAAAAAAAABgcFCAEEAgMJ/8QAMBAAAAUEAQMDAgQHAAAAAAAAAQIDBAUGBxESAAgTIRQiMRVBFhgjMlFXWJaX0dP/2gAIAQEAAD8A+qfDhw4cOHDhw4pXUujRll6Ekbk3Ck1I6n4k7cr10RuouKILLpoFMJEwEwlA6pciADgMj9uI9purywV9aoPSVoa0Wqh6g2O7dqM4p4VuzTKIAXvLKJFIQTiOCBnJtTYDwPLLw4jXlQvM5oZw3sO8pNpVh10QRXqYq5mSaO36oiVEBMJ9fBft5881aqbrjuhO0bQ9tbS0HDyN/qucPY+Shjr92Pp4WDxVo8eudTbAgZRuqKQGMA6e4dsFKfdGF+sBDsQqE7M8oDZIHxmZTFbi40DuCmBxEwE221AwiOMZHPO5w4c55N7x3BujQaUUe2li5W45nplgeFYzbGO9CBAJoJhdGLvvsbGucaDn5Dkz/MN1T/0IVV/e8H/15S7OXCulXhZYbl2JlbbixFD0QPptjI+v337mvpTm001JnfGe4GPgeY3qppKr63spJQFCUy3qGb+sQD5vFuXBEEXRWswzcqkUUUyUpO2ifYRA3tAcFMOCjO6XvPO2avfTdibx0dQkSvclFw4puYo5BVs1UctwDdm7RWDYD4N7FgMIHEwF0KI55Urc1JfOYuVX8XcW38PB0ZFuW6VISTV+C7iWREphVUWKBx7ePZgokJgTGD342Gm8nd/Ze8sLayYd2CpJhUVbnKRCMavnibdFMxzAUy5hUECn7YCJ9BMXbGM/YdSIXpFvV00NKHvFaWloe6F2TSEy7uGLl8nHnmzyaYGEyThUQAibdZMmCgAbic59S7CAUU9QdRdTdXSFplrtPKTgHVtmFZy8UxjY54pHPzujNVGrJ2q2ETJ7pCJlFinEQMfUC5KJJlbS+fUo8s5Ya9VU3dPIL3FuTF0o+iU4JiizPFKuHSCh1BBLu+qMKAHE6ZyEL7QAn7hN6L5dU1+KTnr01jbarJaoKctxPw8c19FERqULFrd1NJ9HyBnOHjoxjqAGzTIpm19xQMIA9dX99br2LnWlx7f3KWqSm5pnKRy9GIxzf1EUsgiZI0uiuRoqp2Gy5NlwXyQBHACICBA2MsPF1ewtzGPK1vEe5b+VQRf/AFsjJm2anKdIg4alapkKKAjkxRPscdvJvgALw2XjryNIxnJV5XdNpxiiqofhaol4ky5jgUP1jJeVAKBR1ARwGxv48mP5G6U/nzfz/JUh/vlJs5Y6JswEsEXXlfVJ9X7Hc/FVSuJbsdrfHZ7w/pbdwdtf3akz+0OJ3WHZ6r7u0RTA0Um5evqPqxhUqkQ2mDxSsu3RKoRRoR2UQ7JxBXYphEA2IACJc7AoSNq7q9QPUVbu69fUVJW9pK1QOnzGKkJVm7fS8ouUpSnErNRVJFFMCh7hUE5xAS6AA7ccLfXBvmXqhre1NxY6mFaS+jp1BSzqJFT1Ldp6grcqbwDeAOqPdMXOMigrpsUB1vPDhxAlrC2gnKyeXDlKCi16lkGhmDqVEpwcqthT7YomOBgHtiUADX4++M+eYQvSf06khI+miWip4sVEvDSDBkVAwINHRsZWSIBsJn8Z2Lgc5H5EeeUr0qdPk5KSctLWvinSk0AjJt1DLCzfKCAB312u/YVX8Bhc5BUDzg3kedqmemawlHLSTimrU06wVl4laBfKJNfc4jlcdxqYRERFI2pck+PHGW3drrfWlgz0zbako6nYo65nIs2CXbRBUwABjAXOAEdQzjjTw4cOccwcLQ9LU9UU/VkRElRl6nVQWlXYqnUO4FBIEki+8wgQhCB4ITUoCY5sbHMI53n/2Q==

 

 

Imagen: data:image/jpg;base64,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 es la mediana de las estimaciones de los parámetros de cola calculadas de conformidad con el artículo 19 para cada uno de los factores de riesgo del segmento;

 

loss0 es la pérdida que se produce cuando la correspondiente perturbación a la baja determinada de conformidad con el artículo 6, apartado 1, letra b), se aplica a cada uno de los factores de riesgo del segmento no modelizable;

 

Imagen: data:image/jpg;base64,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 es la pérdida que se produce cuando la correspondiente perturbación a la baja determinada de conformidad con el artículo 6, apartado 1, letra b), multiplicada por Imagen: data:image/jpg;base64,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 , se aplica a cada uno de los factores de riesgo del segmento no modelizable;

 

 

Imagen: data:image/jpg;base64,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 es la pérdida que se produce cuando la correspondiente perturbación a la baja determinada de conformidad con el artículo 6, apartado 1, letra b), multiplicada por Imagen: data:image/jpg;base64,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 , se aplica a cada uno de los factores de riesgo del segmento no modelizable;

 

c)

cuando el supuesto extremo de perturbación futura sea un supuesto en que la correspondiente perturbación al alza determinada de conformidad con el artículo 6, apartado 1, letra b), se aplique a cada uno de los factores de riesgo del segmento no modelizable, las entidades calcularán el coeficiente de no linealidad con arreglo a la fórmula siguiente:

 

Imagen: data:image/jpg;base64,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

 

donde:

 

Imagen: data:image/jpg;base64,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 ;

 

 

Imagen: data:image/jpg;base64,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

 

 

Imagen: data:image/jpg;base64,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 es la mediana de las estimaciones de los parámetros de cola calculadas de conformidad con el artículo 19 para cada uno de los factores de riesgo del segmento;

 

loss0 es la pérdida que se produce cuando la correspondiente perturbación al alza determinada de conformidad con el artículo 6, apartado 1, letra b), se aplica a cada uno de los factores de riesgo del segmento no modelizable;

 

Imagen: data:image/jpg;base64,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 es la pérdida que se produce cuando la correspondiente perturbación al alza determinada de conformidad con el artículo 6, apartado 1, letra b), multiplicada por Imagen: data:image/jpg;base64,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 , se aplica a cada uno de los factores de riesgo del segmento no modelizable;

 

 

Imagen: data:image/jpg;base64,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 es la pérdida que se produce cuando la correspondiente perturbación al alza determinada de conformidad con el artículo 6, apartado 1, letra b), multiplicada por Imagen: data:image/jpg;base64,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 , se aplica a cada uno de los factores de riesgo del segmento no modelizable.

 

Artículo 19

Cálculo de la estimación del parámetro de cola

Las entidades calcularán la estimación del parámetro de cola para un factor de riesgo no modelizable dado como sigue:

a)

cuando las entidades hayan utilizado el método histórico establecido en el artículo 8 para determinar las perturbaciones calibradas a la baja y al alza de ese factor de riesgo no modelizable y el supuesto extremo de perturbación futura sea la perturbación calibrada a la baja, calcularán la estimación del parámetro de cola con arreglo a la fórmula siguiente:

 

Imagen: data:image/jpg;base64,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

 

donde:

 

Imagen: data:image/jpg;base64,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 ;

 

Ret es la serie temporal de rendimientos de diez días hábiles correspondiente al factor de riesgo no modelizable utilizada en el método histórico establecido en el artículo 8;

 

Imagen: data:image/jpg;base64,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 representa el i-ésimo rendimiento más pequeño de la serie temporal Ret;

 

 

Imagen: data:image/jpg;base64,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 representa la parte entera de Imagen: data:image/jpg;base64,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 ;

 

 

Imagen: data:image/jpg;base64,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 es la estimación de la pérdida esperada condicional de la cola izquierda para la serie temporal Ret calculada de conformidad con el artículo 11, apartado 1;

 

b)

cuando las entidades hayan utilizado el método histórico establecido en el artículo 8 para determinar las perturbaciones calibradas a la baja y al alza de ese factor de riesgo no modelizable y el supuesto extremo de perturbación futura sea la perturbación calibrada al alza, calcularán la estimación del parámetro de cola con arreglo a la fórmula siguiente:

 

Imagen: data:image/jpg;base64,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

 

donde:

 

Imagen: data:image/jpg;base64,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 ;

 

Ret es la serie temporal de rendimientos de diez días hábiles correspondiente al factor de riesgo no modelizable utilizada en el método histórico establecido en el artículo 8;

 

Imagen: data:image/jpg;base64,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 representa el i-ésimo rendimiento más pequeño de la serie temporal  Imagen: data:image/jpg;base64,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 ;

 

 

Imagen: data:image/jpg;base64,/9j/4AAQSkZJRgABAQABLAEsAAD/4gogSUNDX1BST0ZJTEUAAQEAAAoQAAAAAAIQAABtbnRyUkdCIFhZWiAAAAAAAAAAAAAAAABhY3NwQVBQTAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA9tYAAQAAAADTLQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAApkZXNjAAAA/AAAAHxjcHJ0AAABeAAAACh3dHB0AAABoAAAABRia3B0AAABtAAAABRyWFlaAAAByAAAABRnWFlaAAAB3AAAABRiWFlaAAAB8AAAABRyVFJDAAACBAAACAxnVFJDAAACBAAACAxiVFJDAAACBAAACAxkZXNjAAAAAAAAACJBcnRpZmV4IFNvZnR3YXJlIHNSR0IgSUNDIFByb2ZpbGUAAAAAAAAAAAAAACJBcnRpZmV4IFNvZnR3YXJlIHNSR0IgSUNDIFByb2ZpbGUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAdGV4dAAAAABDb3B5cmlnaHQgQXJ0aWZleCBTb2Z0d2FyZSAyMDExAFhZWiAAAAAAAADzUQABAAAAARbMWFlaIAAAAAAAAAAAAAAAAAAAAABYWVogAAAAAAAAb6IAADj1AAADkFhZWiAAAAAAAABimQAAt4UAABjaWFlaIAAAAAAAACSgAAAPhAAAts9jdXJ2AAAAAAAABAAAAAAFAAoADwAUABkAHgAjACgALQAyADcAOwBAAEUASgBPAFQAWQBeAGMAaABtAHIAdwB8AIEAhgCLAJAAlQCaAJ8ApACpAK4AsgC3ALwAwQDGAMsA0ADVANsA4ADlAOsA8AD2APsBAQEHAQ0BEwEZAR8BJQErATIBOAE+AUUBTAFSAVkBYAFnAW4BdQF8AYMBiwGSAZoBoQGpAbEBuQHBAckB0QHZAeEB6QHyAfoCAwIMAhQCHQImAi8COAJBAksCVAJdAmcCcQJ6AoQCjgKYAqICrAK2AsECywLVAuAC6wL1AwADCwMWAyEDLQM4A0MDTwNaA2YDcgN+A4oDlgOiA64DugPHA9MD4APsA/kEBgQTBCAELQQ7BEgEVQRjBHEEfgSMBJoEqAS2BMQE0wThBPAE/gUNBRwFKwU6BUkFWAVnBXcFhgWWBaYFtQXFBdUF5QX2BgYGFgYnBjcGSAZZBmoGewaMBp0GrwbABtEG4wb1BwcHGQcrBz0HTwdhB3QHhgeZB6wHvwfSB+UH+AgLCB8IMghGCFoIbgiCCJYIqgi+CNII5wj7CRAJJQk6CU8JZAl5CY8JpAm6Cc8J5Qn7ChEKJwo9ClQKagqBCpgKrgrFCtwK8wsLCyILOQtRC2kLgAuYC7ALyAvhC/kMEgwqDEMMXAx1DI4MpwzADNkM8w0NDSYNQA1aDXQNjg2pDcMN3g34DhMOLg5JDmQOfw6bDrYO0g7uDwkPJQ9BD14Peg+WD7MPzw/sEAkQJhBDEGEQfhCbELkQ1xD1ERMRMRFPEW0RjBGqEckR6BIHEiYSRRJkEoQSoxLDEuMTAxMjE0MTYxODE6QTxRPlFAYUJxRJFGoUixStFM4U8BUSFTQVVhV4FZsVvRXgFgMWJhZJFmwWjxayFtYW+hcdF0EXZReJF64X0hf3GBsYQBhlGIoYrxjVGPoZIBlFGWsZkRm3Gd0aBBoqGlEadxqeGsUa7BsUGzsbYxuKG7Ib2hwCHCocUhx7HKMczBz1HR4dRx1wHZkdwx3sHhYeQB5qHpQevh7pHxMfPh9pH5Qfvx/qIBUgQSBsIJggxCDwIRwhSCF1IaEhziH7IiciVSKCIq8i3SMKIzgjZiOUI8Ij8CQfJE0kfCSrJNolCSU4JWgllyXHJfcmJyZXJocmtyboJxgnSSd6J6sn3CgNKD8ocSiiKNQpBik4KWspnSnQKgIqNSpoKpsqzysCKzYraSudK9EsBSw5LG4soizXLQwtQS12Last4S4WLkwugi63Lu4vJC9aL5Evxy/+MDUwbDCkMNsxEjFKMYIxujHyMioyYzKbMtQzDTNGM38zuDPxNCs0ZTSeNNg1EzVNNYc1wjX9Njc2cjauNuk3JDdgN5w31zgUOFA4jDjIOQU5Qjl/Obw5+To2OnQ6sjrvOy07azuqO+g8JzxlPKQ84z0iPWE9oT3gPiA+YD6gPuA/IT9hP6I/4kAjQGRApkDnQSlBakGsQe5CMEJyQrVC90M6Q31DwEQDREdEikTORRJFVUWaRd5GIkZnRqtG8Ec1R3tHwEgFSEtIkUjXSR1JY0mpSfBKN0p9SsRLDEtTS5pL4kwqTHJMuk0CTUpNk03cTiVObk63TwBPSU+TT91QJ1BxULtRBlFQUZtR5lIxUnxSx1MTU19TqlP2VEJUj1TbVShVdVXCVg9WXFapVvdXRFeSV+BYL1h9WMtZGllpWbhaB1pWWqZa9VtFW5Vb5Vw1XIZc1l0nXXhdyV4aXmxevV8PX2Ffs2AFYFdgqmD8YU9homH1YklinGLwY0Njl2PrZEBklGTpZT1lkmXnZj1mkmboZz1nk2fpaD9olmjsaUNpmmnxakhqn2r3a09rp2v/bFdsr20IbWBtuW4SbmtuxG8eb3hv0XArcIZw4HE6cZVx8HJLcqZzAXNdc7h0FHRwdMx1KHWFdeF2Pnabdvh3VnezeBF4bnjMeSp5iXnnekZ6pXsEe2N7wnwhfIF84X1BfaF+AX5ifsJ/I3+Ef+WAR4CogQqBa4HNgjCCkoL0g1eDuoQdhICE44VHhauGDoZyhteHO4efiASIaYjOiTOJmYn+imSKyoswi5aL/IxjjMqNMY2Yjf+OZo7OjzaPnpAGkG6Q1pE/kaiSEZJ6kuOTTZO2lCCUipT0lV+VyZY0lp+XCpd1l+CYTJi4mSSZkJn8mmia1ZtCm6+cHJyJnPedZJ3SnkCerp8dn4uf+qBpoNihR6G2oiailqMGo3aj5qRWpMelOKWpphqmi6b9p26n4KhSqMSpN6mpqhyqj6sCq3Wr6axcrNCtRK24ri2uoa8Wr4uwALB1sOqxYLHWskuywrM4s660JbSctRO1irYBtnm28Ldot+C4WbjRuUq5wro7urW7LrunvCG8m70VvY++Cr6Evv+/er/1wHDA7MFnwePCX8Lbw1jD1MRRxM7FS8XIxkbGw8dBx7/IPci8yTrJuco4yrfLNsu2zDXMtc01zbXONs62zzfPuNA50LrRPNG+0j/SwdNE08bUSdTL1U7V0dZV1tjXXNfg2GTY6Nls2fHadtr724DcBdyK3RDdlt4c3qLfKd+v4DbgveFE4cziU+Lb42Pj6+Rz5PzlhOYN5pbnH+ep6DLovOlG6dDqW+rl63Dr++yG7RHtnO4o7rTvQO/M8Fjw5fFy8f/yjPMZ86f0NPTC9VD13vZt9vv3ivgZ+Kj5OPnH+lf65/t3/Af8mP0p/br+S/7c/23////bAEMAAwICAgICAwICAgMDAwMEBgQEBAQECAYGBQYJCAoKCQgJCQoMDwwKCw4LCQkNEQ0ODxAQERAKDBITEhATDxAQEP/AAAsIACMATQEBEQD/xAAbAAACAgMBAAAAAAAAAAAAAAAABwEIBAUGCf/EADAQAAEEAQMDAwEGBwAAAAAAAAECAwQFBgAHEQgSIRMiMQkUFRY2d7UyQUJRYXGR/9oACAEBAAA/APSrcfcrEtqcb/FWZy5bEFUuNAbEOvkTX3pMh1LTLTbEdC3HFLWpKQEpJ5Ot3RXETIaWDfQGpbcawjtymUTIjsV9KFpCgHGXUpcaVwfKFpCgfBAOs7Ro0a4243o2ex3KE4Pf7r4dW5GtbLSaeZeRWZpW7x6SQwpYc5X3J7Rx7u4cc862eZbgYHt1XM3G4GbUOMQJD4isyriyZhMuPFKlBtK3VJBWUpUe0HnhJP8AI646x6l9loSKKXDzJN3W5HYtVMK2oYb9tWCY4+3HbZemREOMMKU682gB1aeSrTQ0luqf8sYN+puG/vMfWNvv1ZYfsdfwMRThuYZtfvRfvWwrMUq1TpFXVBRSqdJAICGu4EDzyohXHgc6zdt+qPBN2d3rTavBa+0sWKrGK3KHb8NpRAWzPQ07FaSFEOla2XkuD2doCVAkKHGu33XyPNsRwK0yXb3C05bd1wakN0v2r7Ouayl1ProaWQR6vpeoWwRwpYSk/OlvbdZG0TO0dbunjUqZkEm/kmppMZiNcXE24Hg1pjH3NPoUQHO4cIHuJKSkqbGCTcxscPqJ+4FHApsikREOWUCDMMpiM+RyptDpSnv48AnjjnngkcE1g64djcd6gM32v2xtymC7djI1RbFoFLsSazWhcV8lJSpYbcCSUE8Ecj+xC7w3eez3g6Sd8Nguoimhu7q7T4vcxrmLNYSsTUsRXVRLJruHCjyls+on5UEOp4DidPPdmpqqPprwWupKyHXREZRgBTHiMIZaSTe1pPCEAJHJPPxqxo0l+qf8sYN+puG/vMfS03N3yx7pR35y/Jd0sfySVR7kVdUugtq+uVOCpkJtxldP2t8qb5Lgfa7gEqXJk+fGlZ9N2bT7X5Vlm3ObbcXuG7lbjz3MxTTmrdEOFQ+kHIiEPElKUNl5xrsV70uHsUARwLs7r5+dscCtMzaxa5ySRDDTUWoqIxflzpLziWmWUJHx3OOIBWfCU8qPgHVRoPTLvjtvmDvWnEraC/3ZsHX5WSYPDhsNwlVjqEJVDr5PZ3psG0NjmSSQ+ruQrlJ99ycEzGu3Aw+ozSpg2cOJcRES2o9nCciSmgofwOsrAUhQPII+PHIJBBNd9/N38KxnqZ2oYtDelOLuXK7h+LjthKYhiXXJRH7nWWFIPepQHsKuP6u3jS8+ov005jaQJfUvsRFV+NKqhm0OR1saOpa76kksqYdSUIHLrrSHFHz5KEjg8toBdW+zKo3T/hcdaVpU3lWAIIWOFAi9rR5B+Dp/DSj6ncUz3KtvqxW2uPRL2+ocposhj10qwTBblJgz2pC2y+pKg3ylsjntP+j8aY+LTL6zxmpsMso2ae5kQ2Xp9czLEpuJIKAXGkvBKQ4Eq5AWEjnjnga2vA5540anUaCkHz5/7o+dJHqSpd28ydw7CcEwGttKF/JaO3vLmReIiu1rUC2iSyG4ykEyCtDCx4Wnj/OncNTo0aNGjRo0aNf/2Q== representa la parte entera de Imagen: data:image/jpg;base64,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 ;

 

 

Imagen: data:image/jpg;base64,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 es la estimación de la pérdida esperada condicional de la cola derecha para la serie temporal Ret calculada de conformidad con el artículo 11, apartado 2;

 

c)

en todos los demás casos, las entidades considerarán la estimación del parámetro de cola

 

Imagen: data:image/jpg;base64,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

 

.
Artículo 20

Cálculo del factor de compensación de la incertidumbre

1.   Cuando la medida del riesgo en un supuesto de tensión con respecto a la cual las entidades estén determinando el factor de compensación de la incertidumbre (UCF) se haya determinado para un único factor de riesgo, el factor de compensación de la incertidumbre será igual a:

 

Imagen: data:image/jpg;base64,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

 

donde:

N es el número de pérdidas de la serie temporal a que se refiere el artículo 2, apartado 1, letra a), inciso iii), a partir de la cual se ha determinado el supuesto extremo de perturbación futura para el factor de riesgo no modelizable de conformidad con dicho artículo.

2.   Cuando la medida del riesgo en un supuesto de tensión con respecto a la cual las entidades estén determinando el factor de compensación de la incertidumbre se haya determinado para un segmento estándar no modelizable, el factor de compensación de la incertidumbre será igual a:

 

Imagen: data:image/jpg;base64,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

 

donde:

N es el número de pérdidas de la serie temporal a que se refiere el artículo 5, apartado 1, letra a), inciso iv), a partir de la cual se ha determinado el supuesto extremo de perturbación futura para el segmento no modelizable de conformidad con dicho artículo.

CAPÍTULO 5
REQUISITOS CUALITATIVOS
Artículo 21

Documentación de los criterios y métodos

Con vistas a desarrollar supuestos extremos de perturbación futura, determinar el supuesto extremo reglamentario de perturbación futura y agregar las medidas del riesgo en un supuesto de tensión, la serie de políticas internas a que se refiere el artículo 325 ter decies, apartado 1, letra e), del Reglamento (UE) n.o 575/2013 preverá que se documente cualquier información necesaria para demostrar que se cumplen los criterios y métodos aplicables establecidos en el presente Reglamento, en particular en relación con los criterios relativos a la aplicación de opciones, las hipótesis realizadas, las condiciones, las etapas necesarias para aplicar las excepciones y las justificaciones, cuando proceda.

CAPÍTULO 6
DISPOSICIONES FINALES
Artículo 22

Entrada en vigor

El presente Reglamento entrará en vigor a los veinte días de su publicación en el Diario Oficial de la Unión Europea.

El presente Reglamento será obligatorio en todos sus elementos y directamente aplicable en cada Estado miembro.

Hecho en Bruselas, el 20 de octubre de 2023.

Por la Comisión

La Presidenta

Ursula VON DER LEYEN

(1)   DO L 176 de 27.6.2013, p. 1.

(2)  Reglamento Delegado (UE) 2022/2059 de la Comisión, de 14 de junio de 2022, por el que se completa el Reglamento (UE) n.o 575/2013 del Parlamento Europeo y del Consejo en lo que respecta a las normas técnicas de regulación que especifican los detalles técnicos de los requisitos en materia de pruebas retrospectivas y atribución de pérdidas y ganancias con arreglo a los artículos 325 ter septies y 325 ter octies del Reglamento (UE) n.o 575/2013 (DO L 276 de 26.10.2022, p. 47).

(3)  Reglamento Delegado (UE) 2022/2060 de la Comisión, de 14 de junio de 2022, por el que se completa el Reglamento (UE) n.o 575/2013 del Parlamento Europeo y del Consejo en lo que respecta a las normas técnicas de regulación que especifican los criterios para evaluar la modelizabilidad de los factores de riesgo en el marco del método de modelos internos (MMI) así como la frecuencia de dicha evaluación con arreglo al artículo 325 ter sexies, apartado 3, de dicho Reglamento (DO L 276 de 26.10.2022, p. 60).

(4)  Reglamento (UE) n.o 1093/2010 del Parlamento Europeo y del Consejo, de 24 de noviembre de 2010, por el que se crea una Autoridad Europea de Supervisión (Autoridad Bancaria Europea), se modifica la Decisión n.o 716/2009/CE y se deroga la Decisión 2009/78/CE de la Comisión (DO L 331 de 15.12.2010, p. 12).

ANÁLISIS

Referencias anteriores
Materias
  • Control financiero
  • Entidades de crédito
  • Entidades financieras
  • Fondos de inversión
  • Normalización
  • Riesgos
  • Sistema financiero

subir

Agencia Estatal Boletín Oficial del Estado

Avda. de Manoteras, 54 - 28050 Madrid