Published
2007-01-01
EVALUACIÓN DE PRONÓSTICOS DEL TIPO DE CAMBIO UTILIZANDO REDES NEURONALES Y FUNCIONES DE PÉRDIDA ASIMÉTRICAS
FORECAST EVALUATION OF THE EXCHANGE RATE USING ARTIFICIAL NEURAL NETWORKS AND ASYMMETRIC COST FUNCTIONS
Keywords:
modelos para series de tiempo, modelos no lineales, tipo de cambio extranjero (es)Time series models, Nonlinear models, Foreign exchange (en)
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Se comparan especificaciones lineales y no lineales (estas últimas expresadas en redes neuronales artificiales) ajustadas a la variación porcentual diaria del tipo de cambio utilizando para ello funciones de costo tradicionales (simétricas) y funciones de pérdida asimétricas. 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.
We compare forecasts obtained via linear vs. non linear specifications. The models are adjusted to the daily percentage change of the exchange rate and the comparison is done using both symmetric and asymmetric cost functions. Results show that the non linear model (which here takes the form of an Artificial Neural Network –ANN) performs better in terms of forecasting ability when evaluated with both types of cost functions. Further more, when using asymmetric costs, the ANN is a much better predictor than its linear counterpart.
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How to Cite
Jalil, M. A., & Misas, M. (2007). FORECAST EVALUATION OF THE EXCHANGE RATE USING ARTIFICIAL NEURAL NETWORKS AND ASYMMETRIC COST FUNCTIONS. Revista Colombiana De Estadística, 30(1), 143-161. https://revistas.unal.edu.co/index.php/estad/article/view/29446
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