Discrete Dynamics in Nature and Society
Volume 2009 (2009), Article ID 250206, 8 pages
Research Article

The Application of SVMs Method on Exchange Rates Fluctuation

1School of Sciences, Beijing Jiaotong University, Beijing 100044, China
2School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China

Received 19 October 2009; Accepted 18 December 2009

Academic Editor: Guang Zhang

Copyright © 2009 Zuoquan Zhang and Qin Zhao. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Technical indicators are very important tools in the analysis of securities investment. In this paper, considering several main technical indicators prevailed in China security market, we predict whether the price of a stock rises or falls with the support vector machines (SVMs). We represent the technical indicators of current four days as input vector. If the price of next day rises, we say that the vector belongs to opposite set, if it falls, we say it belongs to negative set. Studying the samples, the SVMs construct a classification model. Then, based on the data of today and three days before, the SVMs give a prediction of tomorrow price. The experiment shows that the predicting accuracy is all greater than 60%.