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Contrastes de especificación para los modelos de varianza Heterocedástica condicionada

Author

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  • Pérez Rodríguez, Jorge V.

    (Universidad de Barcelona)

  • Murillo Fort, Carlos

    (Universidad Pompeu Fabra)

Abstract

Partiendo de un esquema GARCH (p,q), presentamos una sinopsis de los contrastes estadísticos más relevantes que pueden ser aplicados a los modelos de varianza heterocedástica condicionada, y que pueden extenderse a todos tipo de especificaciones de la misma. Atendiendo a la distinción metodológica de Hendry sobre los contrastes de hipótesis en modelos de regresión, dividimos a éstos en contrastes de especificación (de modelos y de estabilidad de las varianzas) y en contrastes de mala especificación (de no linealidad, heterocedasticidad, curva de impacto de las noticias, capacidad predictiva y otros contrastes. We show a sinopsis of the most relevant tests that are applied to the Autoregresive Conditionaal Heteroscedasstic (ARCH) models, which can be extended to the class of these models. We use Hendry´s methology distinction over hypothesis tests in regression models. In this way, we´ll state a division in specifications tests (models and variances stability) and misspecification tests (non linearity, heteroscedasticity, news impact curve, predict capability and others tests)

Suggested Citation

  • Pérez Rodríguez, Jorge V. & Murillo Fort, Carlos, 1997. "Contrastes de especificación para los modelos de varianza Heterocedástica condicionada," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 7, pages 101-129, Junio.
  • Handle: RePEc:lrk:eeaart:7_2_6
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    References listed on IDEAS

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    1. Brock, W.A. & Dechert, W.D. & LeBaron, B. & Scheinkman, J.A., 1995. "A Test for Independence Based on the Correlation Dimension," Working papers 9520, Wisconsin Madison - Social Systems.
    2. Pagan, Adrian R. & Schwert, G. William, 1990. "Alternative models for conditional stock volatility," Journal of Econometrics, Elsevier, pages 267-290.
    3. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, pages 307-327.
    4. Engle, Robert F & Ng, Victor K, 1993. " Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    5. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    6. Weiss, Andrew A., 1986. "Asymptotic Theory for ARCH Models: Estimation and Testing," Econometric Theory, Cambridge University Press, vol. 2(01), pages 107-131, April.
    7. Holt, Matthew & Aradhyula, Satheesh V., 1990. "Price Risk in Supply Equations: An Application of Garch Time-Series Models to the U.S. Broiler Market," Staff General Research Papers Archive 276, Iowa State University, Department of Economics.
    8. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    More about this item

    Keywords

    ARCH; Lagrange multiplier; Econcompassing Test;

    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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