Evaluación de pronósticos del tipo de cambio utilizando redes neuronales y funciones de pérdida asimétricas

• MUNIR ANDRÉS JALIL ^[1] ; MARTHA MISAS ^[1]
  1. [1] Universidad Nacional de Colombia

     Universidad Nacional de Colombia

     Colombia

     
• Localización: Revista Colombiana de Estadística, ISSN-e 2389-8976, ISSN 0120-1751, Vol. 30, Nº. 1, 2007, págs. 143-161
• Idioma: español
• Títulos paralelos:
  • Forecast Evaluation of the Exchange Rate Using Artificial Neural Networks and Asymmetric Cost Functions
• Enlaces
  • Texto completo
• Dialnet Métricas: 4 Citas
• Resumen
  • español

    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.

  • English

    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.

• Referencias bibliográficas
  • Arango, C.,Misas, M.,López, E.,Hernández, J. N.. (2004). ‘No-linealidades en la demanda de efectivo en Colombia: las redes neuronales como...
  • Azoff, E. M.. (1996). Neural Network. Time Series Forecasting of Financial Markets. ‘Wiley, A Wiley Finance Edition’.
  • Christoffersen, P.,Diebold, F. X.. (1997). ‘Optimal Prediction under Asymmetric Loss’. Econometric Theory. 13.
  • Diebold, F. X.,Gunther, T. A.,Tay, A. S.. (1998). ‘Evaluating Density Forecasts with Applications to Financial Risk Management’. International...
  • Diebold, F. X.,Nasson, J.M.. (1990). ‘Nonparametric Exchange Rate Prediction’. Journal of International Economics. 28.
  • Elliott, G.,Timmermann, A.. (2002). ‘Optimal Forecast Combinations under General Loss Functions and Forecast Error Distributions’, UCSD Working...
  • Frankel, J.,Rose, A.. (1995). Empirical Research on Nominal Exchange Rates, Handbook of International Economics. Elsevier Science. Amsterdam.....
  • Franses, P. H.,Van Dijk, D.. (2000). Non-linear Time Series Models in Empirical Finance. Cambridge University Press..
  • Granger, C.,Teräsvirta, T.. (1993). Modelling Nonlinear Economic Relationships, Advanced Texts in Econometrics. Oxford University Press..
  • Granger, C. W. J.. (1969). ‘Prediction with a Generalized Cost Function’. Operational Research. 20.
  • Granger, C. W. J.,Newbold, P.. (1986). Forecasting Economic Time Series. 2. Academic Press. Orlando..
  • Hornik, K.,Stinchcombe, M.,White, H.. (1989). ‘Multi-Layer Feedforward Networks are Universal Approximators’. Neural Networks. 2.
  • Isard, P.. (1995). Exchange Rate Economics. Cambridge University Press. Cambridge..
  • Kuan, C. M.,Liu, T.. (1995). ‘Forecasting Exchange Rates Using Feedforward and Recurrent Neural Networks’. Journal of Applied Econometrics....
  • Kuan, C. M.,White, H.. (1994). ‘Artificial Neural Networks: An Econometric Perspective’. Econometric Reviews. 13.
  • Meese, R.,Rogoff, K.. (1983). Exchange Rate and International Macroeconomics. University of Chicago Press. Chicago.
  • Meese, R.,Roose, A.. (1991). ‘An Empirical Assessment of Non-Linearities in Models of Exchange Rate Determination’. Review of Econometric...
  • Pesaran, M. H.,Skouras, S.. (2002). A Companion to Economic Forecasting. Blackwell Publishers. Oxford.
  • Plasmans, J.,Verkooijen, W.,Daniels, H.. (1998). ‘Estimating Structural Exchange Rate Models by Artificial Neural Networks’. Applied Financial...
  • Rech, G.. (2002). ‘Forecasting with Artificial Neural Network Models’. SSE/EFI Working paper Series in Economics and Finance. 491.
  • Santana, J. C.. (2006). ‘Predicción de series temporales con redes neuronales: una aplicación a la inflación colombiana’. Revista Colombiana...
  • Stock, J. H.. (2001). ‘Forecasting Economic Time Series’. Blackwell Publishers.
  • Swanson, N. R.,White, H.. (1995). ‘A Model-Selection Approach to Assessing the Information in the Term Structure Using Linear Models and Artificial...
  • Swanson, N. R.,White, H.. (1997). ‘A Model Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural...
  • Swanson, N. R.,White, H.. (1997). ‘Forecasting Economic Time Series Using Flexible versus Fixed Specification and Linear versus Nonlinear...
  • Taylor, M.. (1995). ‘The Economics of Exchange Rates’. Journal of Economic Literature. 83.
  • Tenti, P.. (1996). ‘Forecasting Foreign Exchange Rates Using Recurrent Neural Networks’. Applied Artificial Intelligence. 10.
  • Van Dijk, D.,Teräsvirta, T.,Franses,, P. H.. (2001). Smooth Transition Autoregressive Models – A Survey of Recent Developments, Working paper...
  • Varian, H.. (1974). A Bayesian Approach to Real Estate Assessment. ‘Studies in Bayesian Econometrics and Statistics in Honor of L. F. Savage’....
  • Watson, M.. (2005). Federal Reserve Bank of St. Louis Review. Comentario sobre “What’s Real about the Business Cycle”, Technical report.
  • West, K.,Edison, H.,Cho, D.. (1993). ‘A Utility Based Evaluation of Some Models of Exchange Rate Variability’. Journal of International Economics....
  • Zellner, A.. (1986). ‘Bayesian Estimation and Prediction Using Asymmetric Loss Functions’. Journal of Forecasting. 8.