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机构地区:[1]湖南大学工商管理学院,湖南长沙410082 [2]湖南大学金融与投资管理研究中心,湖南长沙410082
出 处:《系统工程》2013年第7期21-27,共7页Systems Engineering
基 金:国家自然科学基金创新研究群体科学基金资助项目(71221001);国家软科学研究计划项目(2010GXS5B141);教育部长江学者和创新团队发展计划项目(IRT0916);教育部人文社会科学规划青年基金资助项目(09YJC630063);湖南省自然科学基金创新群体资助计划项目(09JJ7002)
摘 要:为准确、科学地度量企业信用风险,在充分考虑现金流风险的基础上,构建了一类基于现金流风险CFaR值的信用风险评估模型。以沪深证券交易所2007~2011年的新增ST公司及其配对公司为样本的实证研究表明,上市公司面临的现金流风险较大,且ST公司和非ST公司的CFaR值存在显著差异。研究同时发现,引入现金流风险CFaR值后,多元判别分析模型、Logistic模型以及支持向量机模型的信用风险预警效果均有一定程度的改进,企业现金流风险是评估和预测信用风险的重要因素。Having fully taken the cash flow risk into consideration, this paper constructs a credit risk assessment model based on the CFaR value of the cash flow risk in order to measure the enterprise credit risk accurately and scientificly. The empirical result, based on the sample consisting of the new ST companies and their matching companies traded on the Shanghai and Shenzhen stock exchanges between 2007 and 2011, firstly shows that the listed companies face a bigger cash flow risk and there exsits a large discrepancy in the CFaR value between the ST companies and the Non-ST companies. Besides, the empirical research further reveals that the credit risk early-warning effects of the multiple discriminate model. The Logistic model and the SVM model are improved to some extent after introducing the CFaR value of the cash flow risk. In addition, the empirical result verifies that the enterprise cash flow risk is one of the important factors involved in evaluating and predicting the enterprise credit risk.
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