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Medidas De Riesgo, Caracteristicas 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, Caracteristicas Y Técnicas De Medición: Una Aplicación Del Var Y El Es A La Tasa Interbancaria De Colombia," Borradores de Economia 3198, Banco de la Republica.
    • Handle: RePEc:col:000094:003198
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    References listed on IDEAS

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    Cited by:

    1. Charle Augusto Llondono, 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, vol. 29(64), pages 62-109, July.
    2. Bernardo León & Andrés Mora, 2011. "CDS: relación con índices accionarios y medida de riesgo," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 29(64), pages 178-211, July.
    3. 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.
    4. 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.

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    More about this item

    Keywords

    Riesgo de Mercado;

    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

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