TITLE:
Bankruptcy Prediction Using Machine Learning
AUTHORS:
Nanxi Wang
KEYWORDS:
Support Vector Machine, Autoencoder, Neural Network, Bankruptcy, Machine Learning
JOURNAL NAME:
Journal of Mathematical Finance,
Vol.7 No.4,
November
17,
2017
ABSTRACT: With improved machine learning models, studies on bankruptcy prediction show improved accuracy. This paper proposes three relatively newly-developed methods for predicting bankruptcy based on real-life data. The result shows among the methods (support vector machine, neural network with dropout, autoencoder), neural network with added layers with dropout has the highest accuracy. And a comparison with the former methods (logistic regression, genetic algorithm, inductive learning) shows higher accuracy.