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Evaluación de pronósticos del tipo de cambio utilizando

Author

Listed:
  • Munir A. Jalil. B
  • Martha Misas

Abstract

El presente trabajo compara especificaciones lineales y no lineales (expresadas en redes neuronales artificiales) ajustadas a la variación porcentual diaria del tipo de cambio utilizando para ello funciones de costo tradicionales (simétricas) a la vez que se introduce el análisis asimétrico. Los resultados muestran que las redes neuronales permiten obtener mejores pronósticos con ambos tipos de funciones de costos. Sin embargo, es de anotar que cuando se evalúan los pronósticos con funciones asimétricas, el modelo no lineal supera ampliamente a su contraparte lineal.

Suggested Citation

  • Munir A. Jalil. B & Martha Misas, 2006. "Evaluación de pronósticos del tipo de cambio utilizando," Borradores de Economia 2636, Banco de la Republica.
    • Handle: RePEc:col:000094:002636
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    Citations

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    Cited by:

    1. Carlos León & Fabio Ortega, 2018. "Nowcasting Economic Activity with Electronic Payments Data: A Predictive Modeling Approach," Revista de Economía del Rosario, Universidad del Rosario, vol. 21(2), pages 381-407, December.
    2. José Mauricio Salazar Sáenz, 2009. "Evaluación de pronóstico de una red neuronal sobre el PIB en Colombia," Borradores de Economia 575, Banco de la Republica de Colombia.
    3. José Mauricio Salazar Sáenz, 2009. "Evaluación de pronóstico de una red neuronal sobre el PIB en Colombia," Borradores de Economia 5934, Banco de la Republica.
    4. María Clara Aristizábal Restrepo, 2006. "Evaluación asimétrica de una red neuronal artificial:Aplicación al caso de la inflación en Colombia," Borradores de Economia 377, Banco de la Republica de Colombia.
    5. Gerencia de Riesgo Asobancaria, 2011. "Estimación de la Carga Financiera en Colombia," Temas de Estabilidad Financiera 056, Banco de la Republica de Colombia.

    More about this item

    Keywords

    Tipo de cambio; redes neuronales artificiales; evaluación de pronóstico;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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