基于主成分判别分析的制造业上市公司财务危机预警机制的研究  

Research on Early Warning Mechanism of Financial Crisis of Manufacturing Listed Companies Based on Principal Component Discriminant Analysis

作　　者：戈俏梅[1] 徐碧莹 GE Qiaomei;XU Biying(Anhui University Of Finance,Bengbu Anhui 233030,China)

机构地区：[1]安徽财经大学会计学院,安徽蚌埠233030

出　　处：《长沙大学学报》2019年第3期38-41,共4页Journal of Changsha University

基　　金：安徽省哲学社会科学规划一般项目"嵌入商业模式的财务失败预测模型构建";编号:AHSKY2017D08

摘　　要：以制造业上市公司为研究对象,选取2017年被退市警告的32家公司作为财务危机公司,按照1∶1配对原则随机选取32家财务正常公司作为研究样本,以公司发生财务危机前两年(2015年)的财务指标为基础,运用主成分分析法对这64家样本企业的财务指标提取主成分,再通过多元判别分析方法构建制造行业上市公司财务预警模型。最后,利用随机选取的40家制造企业2016年的财务数据对模型的有效性进行实证检验。研究结果表明,所建模型对财务风险预测的准确度较高,能够有效地为制造业企业进行财务预警。Taking the listed companies in the manufacturing industry as the research object, selecting 32 companies that have been delisted in 2017 as financial crisis companies, randomly selecting 32 financial normal companies as research samples according to the 1:1 matching principle, and based on the financial indicators of the year (2015) before the financial crisis, this paper extracts the principal components of the financial indicators of the 64 sample enterprises with the principal component analysis method , and then the financial early warning model of the listed companies in the manufacturing industry is constructed by the multivariate discriminant analysis method. Finally, the randomly selected financial data of 40 manufacturing companies in 2016 are used to conduct an empirical test on the validity of the model. The research results show that the model has high accuracy in financial risk prediction and can effectively provide financial warning to manufacturing enterprises.

关 键 词：制造业 财务预警 主成分分析 多元判别分析 

分 类 号：F275.2[经济管理—企业管理]