Abstract:
Corporate credit rating has an important role in reducing asymmetric information between investors and borrowers and assisting investors as a signal of the entities’ performance and creditworthiness for making appropriate investment decisions in a company’s assets. The economic distress has negatively affected various businesses and resulted in company rating transitions. This led to a problem in adjusting investment strategy and a serious loss as there is a lack of time between officially announced credit rating transitions and real transition. This study provides alternative methods for credit rating prediction by applying machine learning models; Support Vector Machine (SVM), Linear Regression, and Deep Neural Network (DNN). The result has shown that the Deep Neural Network model presents the comparable performance to other models.
