Application of SVM in Financial Research
2009
Based on the structural risk minimization, support vector machine is a new method of data mining. Since it has effectively solved complicated problems of classification and prediction, it has been widely used in many cross-disciplinary fields. This paper has reviewed and analyzed SVM’s application to the classification and prediction in the financial field. It has a promising future of applying to company's credit rating, early warning, stock prices forecast and so on. However, we hold that the correct selection of kernel and different sub-assembly function, as well as parameters, is the key point to optimize the application of SVM.
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