Financial Risk Early Warning Model of Industrial Listed Enterprises Based on Deep Learning

. In this paper, the public financial indicators of 156 listed industrial enterprises in China Stock Market in T-2 year(2017) are used to predict the company financial status in T year(2019). Based on the feature extraction of Random Forest, a double LSTM financial risk early warning model is built through Keras framework. Machine learning algorithms including LR, SVM, KNN and NBC are set as baseline models. To reduce the influence of unbalanced data on the model, the G-mean is introduced as the comprehensive measure of the model. The result shows that G-mean of RF-LSTM on the test set is much higher than that of machine learning model which verifies the practicability of the RF-LSTM model.