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Medidas de Riesgo, Características y Técnicas de Medición: Una Aplicación del VAR y el ES a la Tasa Interbancaria de Colombia

Author

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  • Luis Fernando Melo Velandia

    ()

  • Oscar reinaldo Becerra Camargo

    ()

Abstract

En este documento se describen en detalle diversas metodologías que permiten calcular dos medidas utilizadas para cuantificar el riesgo de mercado asociado a un activo financiero: el valor en riesgo, VaR y el Expected Shortfall, ES. Los métodos analizados se dividen en dos grupos. En el primer grupo, compuesto por las metodologías de normalidad, simulación histórica y teoría del valor extremo (EVT), no se modelan las dependencias existentes en el primer y segundo momento condicional de la serie. En el segundo grupo, las metodologías ARMA-GARCH y ARMA-GARCH-EVT modelan los dos tipos de dependencias, mientras RiskMetrics® modela solo la segunda. Estas metodologías son aplicadas a las variaciones diarias de la tasa interbancaria para el periodo comprendido entre el 16 de abril de 1995 y el 30 de diciembre de 2004. El desempeño o backtesting del VaR calculado para diferentes metodologías en los años 2003 y 2004 muestra que las mejores son aquellas que modelan la dependencia de la varianza condicional, tales como los modelos RiskMetrics®, ARMA-GARCH y ARMA-GARCH-EVT. Las técnicas con el peor desempeño son la de simulación histórica, la EVT sin modelar dependencia y la basada en el supuesto de normalidad.

Suggested Citation

  • Luis Fernando Melo Velandia & Oscar reinaldo Becerra Camargo, 2005. "Medidas de Riesgo, Características y Técnicas de Medición: Una Aplicación del VAR y el ES a la Tasa Interbancaria de Colombia," Borradores de Economia 343, Banco de la Republica de Colombia.
  • Handle: RePEc:bdr:borrec:343
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    References listed on IDEAS

    as
    1. Luis Fernando Melo Velandia & Martha Alicia Misas Arango, 2004. "Modelos Estructurales de Inflación en Colombia: Estimación a través de Mínimos Cuadrados Flexibles," BORRADORES DE ECONOMIA 003244, BANCO DE LA REPÚBLICA.
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    Cited by:

    1. Restrepo E., María Isabel, 2012. "Estimating Portfolio Value at Risk with GARCH and MGARCH models," Perfil de Coyuntura Económica, Universidad de Antioquia - CIE, issue 19, pages 77-92, July.
    2. repec:col:000093:017470 is not listed on IDEAS
    3. Charle Augusto Llondoño, 2011. "Regresión del cuantil aplicada al modelo de redes neuronales artificiales. Una aproximación de la estructura CAVIAR para el mercado de valores colombiano," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República - ESPE, vol. 29(64), pages 62-109, July.
    4. Bernardo León & Andrés Mora, 2011. "CDS: relación con índices accionarios y medida de riesgo," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 29(64), pages 178-211, July.
    5. Daniel Mariño-Ustacara & Luis Fernando Melo-Velandia, 2016. "Relación entre los valores en riesgo de los principales mercados financieros colombianos: un enfoque a través de modelos multivariados de regresión cuantílica," Borradores de Economia 975, Banco de la Republica de Colombia.
    6. Luis Melo Velandia & Luis Fernando Melo Velandia, 2019. "Regresión cuantílica dinámica para la medición del valor en riesgo: Una aplicación a datos colombianos," Revista Cuadernos de Economía, Universidad Nacional de Colombia -FCE - CID, vol. 38(76), pages 23-50, January.
    7. Karoll Gómez Portilla & Santiago Gallón Gómez, 2007. "Distribución condicional de los retornos de la tasa de cambio colombiana: un ejercicio empírico a partir de modelos GARCH multivariados," Revista de Economía del Rosario, Universidad del Rosario, December.

    More about this item

    Keywords

    Riesgo de Mercado; valor en riesgo; Expected shortfall; teoría del valor extremo; modelos GARCH; backtesting;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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