基于CFaR模型与Logistic回归的财务困境预警研究
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引用本文:谢赤,赵亦军,李为章.基于CFaR模型与Logistic回归的财务困境预警研究[J].财经理论与实践,2014,(1):57-62
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作者单位
谢赤,赵亦军,李为章 (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) 
中文摘要:从现金流风险角度出发,对企业财务困境进行预警研究:首先构建一个基于企业内部环境、宏观经济政策、货币政策及财政政策等因素的CFaR模型,识别出期望现金流及风险现金流;然后以这两个指标作为预警变量,构建一个二元Logistic财务困境预警模型;最后选取27家中国证券市场中代表陷入财务困境的ST公司及配对的财务良好的非ST公司作为样本进行实证研究。结果表明,所构建的CFaR模型能较好地度量两类上市公司的现金流状况,且两类公司的期望现金流和风险现金流水平存在显著的差异;二元Logistic预警模型能较好地实现对上市公司财务风险的预警,对两类公司的预警正确率分别达到85.2%和81.5%。
中文关键词:财务困境  现金流风险  Logistic模型  CFaR模型
 
Research on Corporate Financial Distress Warning Based on CFaR Model and Logistic Regression Model
Abstract:Corporate stakeholders attach great importance to financial distress . In this paper, we investigate financial distress warning from the perspective of cash flow risk. First of all, we construct a Cash Flow at Risk (CFaR) model, considering the risk factors from corporate internal and external environment. Then, we get the expected cash flow and the risk cash flow, use them as warning variables and construct a bivariate logistic financial distress warning model. 27 ST listed companies, who are in financial distress, and 27 paired listed companies are selected as samples. The results show the CFaR model performs well in measuring the cash flow conditions of the sample companies. The expected cash flow and the risk cash flow of the two types of companies have large differences. What's more, the bivariate logistic financial distress warning model also performs well. Specifically, its warning accuracy rates of the ST companies and the paired companies reach to 85.2% and 81.5% respectively.
keywords:Financial distress  Cash Flow at Risk  Logistic model  CFaR model
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