ABSTRACT
This article proposes a hybrid model by combining zero-price probability model with long short-term memory (ZPP-LSTM) to estimate corporate default probabilities. The ZPP-LSTM model enhances the time-series data forecast by introducing LSTM in ZPP model, which can better estimate the corporate default probabilities in the industry sensitive to an uncertain environment. The full samples of Chinese listed companies in construction and real estate industries are selected to evaluate the performance of ZPP-LSTM model. The results show that our proposed model outperforms other benchmark models in terms of the default probability estimation.
Acknowledgments
We would like to thank an anonymous referee for providing many constructive comments and suggestions that helped us significantly improve the article. We are also grateful for the comments from Dr. Timothy Wang.
Disclosure statement
No potential conflict of interest was reported by the authors.