An Enterprise Default Prediction Model Based on the Indicators Selected by Average Accuracy and Bayesian Information Criterion-Taking China's Small Listed Companies as an Example

Abstract

Abstract: Predicting potential default of small listed companies (small listcos for short) is of great significance for banks to issue loans, for investors to make an informed decision and for regulatory authorities to supervise the market. Based on the big data perspective, this paper selects a set of indicators from more than 300 indicators including small listcos' financial and non-financial indicators and macro-economic indicators, and uses the set of indicators to establish a default prediction model for China's small listcos. The contributions of this paper are as follows:in the first stage, the minimum value of Gini of the indicator Xi is used as the node to divide the small listcos into defaulting ones and non-defaulting ones; a set of features is used to construct a decision tree and then multiple sets of indicators are used to construct multiple decision trees, which are used to calculate the importance value VI (Xi), with indicators of high importance value retained; a set of indicators with the minimum Bayesian criterion value are selected from the retained indicators. The research shows that:(1) The indicators selected in this study can predict the default status of small listcos and conform to the principle of credit 5C. The indicator that has a key impact on the default status of small listcos in the next 0-5 years is “retained earnings per share”; the indicator that has a key impact on the short-term default forecast of small listcos is “other receivables”; an indicator that has a key im-pact on default forecasts is the “Industry Sentiment Index”; (2) the comparative analysis of multiple data sets, the comparative analysis of multi-index selection and the comparative analysis of multiple models show that the index selection method in this paper is significantly better than other three typical methods, and the results are robust; (3) small listcos in the eastern region have the highest credit qualifi-cation compared with those in other geographical regions, and non-backdoor-listed small listcos have the highest credit qualification com-pared with those listed in other ways.

Key words: average accuracy, small listcos, default prediction, indicator selection

Dong Bingjie, Zhou Ying, Li Jizhe, Wang Shanshan. An Enterprise Default Prediction Model Based on the Indicators Selected by Average Accuracy and Bayesian Information Criterion-Taking China's Small Listed Companies as an Example[J]. Management Review, 2024, 36(5): 12-24.

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