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Los efectos de largo plazo de la asimetría y persistencia en la predicción de la volatilidad: evidencia para mercados accionarios de América Latina

Author

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  • Raúl de Jesús Gutiérrez

    () (Universidad Autónoma del Estado de México, México)

  • Edgar Ortiz

    (Universidad Nacional Autónoma de México, México)

  • Oswaldo García Salgado

    (Universidad Autónoma del Estado de México, México)

Abstract

Este trabajo propone una extensión al modelo CGARCH a fin de recoger las características de asimetría y persistencia de largo plazo, e investiga sus efectos en el modelado y predicción de la volatilidad condicional de los mercados accionarios de la región de América Latina en el periodo del 2 de enero de 1992 al 31 de diciembre de 2014. En el análisis dentro de la muestra, los resultados estimados de la familia de modelos CGARCH indican la presencia de efectos asimétricos significativos y persistencia de corto y largo plazos en la estructura de la volatilidad de los rendimientos accionarios. Los resultados empíricos también muestran que el uso de medidas simétricas y asimétricas y la prueba estadística de Hansen (2005) son excelentes alternativas para evaluar el poder predictivo de los modelos CGARCH asimétricos. La incorporación de la asimetría y persistencia de largo plazo en la ecuación de la varianza mejora significativamente las predicciones de la volatilidad fuera de la muestra para los mercados accionarios emergentes de Argentina y México.

Suggested Citation

  • Raúl de Jesús Gutiérrez & Edgar Ortiz & Oswaldo García Salgado, 2017. "Los efectos de largo plazo de la asimetría y persistencia en la predicción de la volatilidad: evidencia para mercados accionarios de América Latina," Contaduría y Administración, Accounting and Management, vol. 62(4), pages 1063-1080, Octubre-D.
  • Handle: RePEc:nax:conyad:v:62:y:2017:i:4:p:1063-1080
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    More about this item

    Keywords

    Volatilidad asimétrica; Mercados accionarios emergentes; Medidas de errores simétricas y asimétricas; Prueba de poder predictivo superior;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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