[1]肖叶宇,张 闪.基于随机生存森林的企业财务危机研究[J].南京师大学报(自然科学版),2021,44(04):1-6.[doi:10.3969/j.issn.1001-4616.2021.04.001]
　Xiao Yeyu,Zhang Shan.Research on Financial Crisis of Enterprises Based on Random Survival Forest[J].Journal of Nanjing Normal University(Natural Science Edition),2021,44(04):1-6.[doi:10.3969/j.issn.1001-4616.2021.04.001]
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基于随机生存森林的企业财务危机研究()
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《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

卷:
第44卷
期数:
2021年04期
页码:
1-6
栏目:
·数学·
出版日期:
2021-12-15

文章信息/Info

Title:
Research on Financial Crisis of Enterprises Based on Random Survival Forest
文章编号:
1001-4616(2021)04-0001-06
作者:
肖叶宇1; 张 闪2
(1.吉林大学数学学院,吉林 长春 130012)(2.南京财经大学应用数学学院,江苏 南京 210023)
Author(s):
Xiao Yeyu1; Zhang Shan2
(1.College of Mathematics,Jilin University,Changchun 130012,China)(2.School of Applied Mathematics,Nanjing University of Finance and Economics,Nanjing 210023,China)
关键词:
随机生存森林; 生存分析; 财务危机预警
Keywords:
Random Survival Forest; survival analysis; financial crisis early warning
分类号:
O213
DOI:
10.3969/j.issn.1001-4616.2021.04.001
文献标志码:
A
摘要:
以沪深两市A股制造业上市公司为样本,将随机生存森林模型引入企业财务危机研究中去. 通过计算两种度量下变量重要性排名,发现营业收入增长率和息税前利润对财务危机的影响最大. 随后将随机生存森林与Cox、后向逐步Cox和Lasso-Cox模型进行对比,随机生存森林的预测性能要优于3种Cox模型. 同时结合随机生存森林下的生存函数和累积风险函数,对公司被特别处理的时间进行分析,结果显示模型有很好的预警功效,可以为各利益相关方的决策提供依据.
Abstract:
Taking Shanghai and Shenzhen A-share manufacturing listed companies as a sample,the Random Survival Forest model is introduced into the research on corporate financial crisis. It is found that the growth rate of operating income and the profit before interest and tax have the greatest impact on the financial crisis by calculating the ranking of the importance of variables under the two measures. Subsequently,the Random Survival Forest was compared with Cox model,Cox model with backward stepwise variable selection and Lasso-Cox models. The prediction performance of the Random Survival Forest is better than the three Cox models. At the same time,combined with the survival function and cumulative hazard function under the random survival forest,the company is analyzed for the time when the company is ST. The results show that the model has a good early warning function,which can provide a basis for the decision-making of various stakeholders.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2021-03-12.
基金项目:国家自然科学基金项目(11601224).
通讯作者:张闪,博士,副教授,研究方向:生物数学. E-mail:shanzhang86@163.com
更新日期/Last Update: 2021-12-15