Author(s)

Nanxi Wang

Shanghai Starriver Bilingual School, Shanghai, China.

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.

Support Vector Machine, Autoencoder, Neural Network, Bankruptcy, Machine Learning

Wang, N. (2017) Bankruptcy Prediction Using Machine Learning. Journal of Mathematical Finance, 7, 908-918. doi: 10.4236/jmf.2017.74049.