Research of Financial Early-Warning Model on Evolutionary Support Vector Machines Based on Genetic Algorithms

Abstract EN

A support vector machine is a new learning machine; it is based on the statistics learning theory and attracts the attention of all researchers.

Recently, the support vector machines (SVMs) have been applied to the problem of financial early-warning prediction (Rose, 1999).

The SVMs-based method has been compared with other statistical methods and has shown good results.

But the parameters of the kernel function which influence the result and performance of support vector machines have not been decided.

Based on genetic algorithms, this paper proposes a new scientific method to automatically select the parameters of SVMs for financial early-warning model.

The results demonstrate that the method is a powerful and flexible way to solve financial early-warning problem.