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Modelos autorregresivos para la varianza condicionada heteroscedastica (ARCH)

Author

Listed:
  • Marc Saez Zafra

    (Departamento de economía. Universidad Pompeu Fabra)

  • Jorge V. Pérez Rodríguez

    (Departamento de Econometría. Universidad de Barcelona.)

Abstract

En el presente trabajo se introduce al lector en los modelos autorregresivos para la varianza condicionada heterocedástica, incidiendo en los problemas que plantean los esquemas más sencillo y sugiriendo diversas soluciones. Se describe el concepto, las hipótesis y los modelos que explican la varianza condicionada en el tiempo desde diversas perspectivas del análisis estadístico: relación lineal o no lineal entre las variables y métodos de estimación de los parámetros. Finalmente, se discuten diversos contrastes que permiten escoger entre diversas especificaciones alternativas. In this paper the Autoregressive Conditional Heteroskedasticity (ARCH) models are introduced to the reader. The problems implied by their different parameterizations are pointed out and the corresponding solutions are suggested. Several statistical perspectives are used to explain the concept, the assumptions and the models that explain the temporal behaviour of the conditional variances. The paper exposed lineal and non-lineal relationships and several methods of estimation of the parameters of the models. Finally, some tests that allow to choose between alternative specifications are described.

Suggested Citation

  • Marc Saez Zafra & Jorge V. Pérez Rodríguez, 1994. "Modelos autorregresivos para la varianza condicionada heteroscedastica (ARCH)," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 2, pages 71-106, Diciembre.
  • Handle: RePEc:lrk:eeaart:2_3_4
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    References listed on IDEAS

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    More about this item

    Keywords

    ARCH Models; Conditional and unconditional variances; time-varying factors;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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