Journal of Economic Theory and Econometrics: Journal of the Korean Econometric Society
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Journal of Economic Theory and Econometrics
JETEM/계량경제학보/計量經濟學報/JKES
Journal of the Korean Econometric Society

Predicting Exchange Rates by Support Vector Regression

Vol.20, No.2, June , 65–81



  •   (Department of Economics,Fudan University)

  •   ( School of Economics and Trade, Kyungpook National University)

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Abstract  

In recent years, support vector regression (SVR), a novel neural network technique, has been successfully used for financial forecasting. This paper deals with the application of SVR in exchange rate forecasting. Based on SVR, a nonparametric autoregressive (AR) model is applied to forecasting the daily exchange rates of two currencies (South Korea Won and Singapore Dollar) against the US dollar. The empirical results show that under various forecasting horizons, SVR performs better than the random walk model, parametric AR model and the nonparametric AR model estimated by neural network, based on the criteria of two evaluation metrics and three encompassing tests. No structured way being available to choose the free parameters of SVR, the sensitivity of the forecasting performance is also examined to the free parameters.


Keywords
   Support Vector Regression, nonparametric AR model, forecasting exchange rates

JEL classification codes
   C45, G17
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