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This paper presents a new kind of nonlinear combination method to predict the exchange rate. The method possesses several characters as follows: (1) the short, medium and long-term influences are considered comprehensively; (2) the different singular methods are nonlinearly combined according to their characteristics; (3) Some original data is taken as the inputs of network with the forecasted values;...
We illustrate the AutoRegessive/Generalised Conditionally Heterosscedastic (ARCH-GARCH) methodology on the developing a forecast model for exchange rates time series of the Czech crown (CZK) against the Slovak crown (SKK) and make comparisons the forecast accuracy with the class of Radial Basic Function Neural neural network RBF NN models. To illustrate the forecasting performance of these approaches...
A novel forecasting model of foreign exchange market based on least squares support vector machine (LS-SVM) is proposed in this paper. The experiment on the prediction of four kinds of daily exchange rate recorded is carried out. Grid search method is used to determine the LS-SVM parameters automatically in the forecasting process. The results show the precision of fitting and forecasting are very...
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