Credit Rating Analysis with Support Vector Machines Optimized by Genetic Algorithm

In this paper we apply a relatively new learning algorithm, support vector machines optimized by genetic algorithms (GA-SVM) to the credit-rating prediction problem and expect to improve prediction accuracy by adopting this new algorithm. Based on the result, we conducted a market analysis on the determining factors in the China markets. By determining what information was actually used by expert financial analysts, these studies can help users capture fundamental characteristics of different financial markets.