Financing Risk Prediction of China's Listed Company based on GA-SVR Model

Improving the prediction accuracy of corporate financing risk is of great significance for promoting corporate financing and alleviating corporate financing constraints.In this paper,the listed companies in China's listed company are taken as the research object,the financing risk forecasting index is screened by using rough set theory(RS),the parameters of support vector regression(SVR)model are optimized by genetic algorithm(GA),and GA-SVR model predicts financing risks of listed companies.The research shows that the 17 financing risk forecasting indexes obtained by rough set theory screening have a strong ability of distinguishing whether an enterprise is abnormal or not; the scale of assets plays a crucial role in the risk prediction of listed companies; SVR model has good prediction accuracy and robustness.