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Cuadernos de Administración
versión impresa ISSN 0120-3592
Resumen
MENDEZ SAYAGO, Jhon Alexander. Nominal exchange rate microstructure and dynamics in Colombia: an approach using artificial neural networks and neural diffusion systems. Cuad. Adm. [online]. 2008, vol.21, n.36, pp.11-35. ISSN 0120-3592.
This article presents the results of empirical assessments of the nominal exchange rate in Colombia, conducted using linear specifications (distributed lag model) and non-linear specifications (artificial neural networks and neural diffusion systems). All of the econometric specifications employ order flow as the determinant for the exchange rate, the most representative variable for models that attempt to explain the nominal exchange rate, supported by the exchange market microstructure. The forecast error measurements used to assess the predictive ability of the models evidenced that linear and non-linear models had an advantage over a random path models, attributable to the order flow. Nonlinear models were somewhat superior to the linear model in terms of the root mean square error, Theils coefficient, and the percentage of predicted correct changes, but the difference was so slight that it does not enable confirming the hypothesis that the exchange rate generation process is non-linear.
Palabras clave : exchange rate; order flow; artificial neural networks; neural diffusion systems.