Title :
Forecasting exchange rate using support vector machines
Author :
Cao, Ding-Zhou ; Pang, Su-Lin ; Bai, Yuan-Huai
Author_Institution :
Dept. of Math., Jinan Univ., Guangzhou, China
Abstract :
Recently, support vector machines is a focus research field in the world, support vector regression which is used as a technology to solve the regression problems have the advantages of global optimal solutions, the solutions avoiding overtraining and so on. This paper establishes a model of exchange rate prediction based on support vector machines, collects the daily data of USD/GBP exchange rate and uses these data to train the model and checks the predictive power of this model. The result shows that SVM model has some predictive power; it can be used to forecast finance time series. In addition, this article also discusses the issue on finding the optimal parameters of SVM and does lots of experiments to find them.
Keywords :
exchange rates; forecasting theory; optimisation; regression analysis; support vector machines; time series; SVM; exchange rate forecasting; finance time series; support vector machines; support vector regression; Artificial neural networks; Chaos; Exchange rates; Finance; Mathematics; Neural networks; Optimal control; Predictive models; Risk management; Support vector machines; Exchange rate forecasting; SVM; SVR; Time series prediction;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527538
