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大中型煤炭企业信用风险评估体系研究
引用本文:顾清华,宋思远,张新生,暴子旗.大中型煤炭企业信用风险评估体系研究[J].中国矿业,2022,31(5).
作者姓名:顾清华  宋思远  张新生  暴子旗
作者单位:西安建筑科技大学,西安建筑科技大学,西安建筑科技大学,西安建筑科技大学
基金项目:国家社会科学基金(18XGL010),陕西省教育厅2020年度重点科学研究计划(20JT033)
摘    要:大中型煤炭企业具有与市场关联度高、风险损失大等特点,一旦出现信用风险,对企业以及社会的影响都是巨大的。为了能够准确识别煤炭企业的信用风险,本文以上市煤炭企业为研究对象,提出基于Filter-Wrapper两阶段特征选择的大中型煤炭企业信用风险评估模型。首先针对大中型煤炭企业的特点,在通用指标选择上结合煤炭企业风险因素提出两个新指标:抗风险能力、煤炭及加工产品业务销售毛利率;然后使用Filter-Wrapper两阶段特征选择算法用来筛选冗余特征,从而构建信用风险预测模型。实验表明所提出模型与筛选前相比具有更高的预测准确性,同时对信用风险违约样本识别率也更高,验证了模型与所提指标的有效性,对大中型煤炭企业的信用风险识别具有重要意义。

关 键 词:煤炭企业  信用风险  指标体系  Filter-Wrapper  预测
收稿时间:2021/9/16 0:00:00
修稿时间:2022/5/10 0:00:00

Study on the Credit Risk Assessment for Large and Medium-sized Coal Enterprises
GU Qinghu,SONG Siyuan,ZHANG Xinsheng and BAO Ziqi.Study on the Credit Risk Assessment for Large and Medium-sized Coal Enterprises[J].China Mining Magazine,2022,31(5).
Authors:GU Qinghu  SONG Siyuan  ZHANG Xinsheng and BAO Ziqi
Abstract:Large and medium-sized coal companies have the characteristics of high market relevance and large risk losses. Once credit risk occurs, the impact on the company and society will be huge. To accurately identify the credit risk of coal companies, this paper takes listed coal companies as the research object, and proposes a credit risk assessment model for large and medium-sized coal companies based on Filter-Wrapper two-stage feature selection. First of all, according to the characteristics of large and medium-sized coal enterprises, two new indicators are proposed in combination with the risk factors of coal enterprises in the selection of general indicators: anti-risk ability, gross profit margin of coal and processed products business sales; then the Filter-Wrapper two-stage feature selection algorithm is used to filter redundant features to build a credit risk prediction model. The experimental results show that the proposed model has higher prediction accuracy than before screening, and higher recognition rate of credit risk default samples. It verifies the effectiveness of the model and the proposed indicators, which is of great significance to the credit risk identification of large and medium-sized coal enterprises.
Keywords:Coal enterprise  Credit risk  Index system  Filter-Wrapper  Prediction
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