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- W2807726864 abstract "Resumen El objetivo de esta investigación es proponer un modelo de volatilidad multivariable, el cual combina la propiedad de la distribución α-estable para ajustar colas pesadas con el modelo GARCH para capturar clúster de volatilidad. El supuesto inicial es que los rendimientos siguen una distribución sub-Gaussiana, la cual es un caso particular de las distribuciones estables multivariadas. El modelo GARCH propuesto se aplica en la estimación del VaR a un portafolio compuesto por cinco activos que cotizan en la Bolsa Mexicana de Valores (BMV). En particular, se compara el desempeño del modelo propuesto con la estimación del VaR obtenida bajo la hipótesis multivariada Gaussiana, t-Student y Cauchy durante el período de la crisis financiera de 2008. Abstract The purpose of this investigation is to propose a multivariate volatility model that takes into consideration time varying volatility and the property of the α-stable sub-Gaussian distribution to model heavy tails. The principal assumption is that returns follow a sub-Gaussian distribution, which is a particular multivariate stable distribution. The proposed GARCH model is applied to a Value at Risk (VAR) estimation of a portfolio composed by 5 companies listed in the Mexican Stock Exchange Index (IPC) and compared with the one obtained using the normal multivariate distribution, t-Student and Cauchy. In particular, we examine performances during the financial crisis of 2008." @default.
- W2807726864 created "2018-06-21" @default.
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- W2807726864 date "2018-04-25" @default.
- W2807726864 modified "2023-10-03" @default.
- W2807726864 title "ESTIMACIÓN DEL VAR MEDIANTE UN MODELO CONDICIONAL MULTIVARIADO BAJO LA HIPÓTESIS Α-ESTABLE SUB-GAUSSIANA" @default.
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- W2807726864 doi "https://doi.org/10.29105/ensayos37.1-2" @default.
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