基于支持向量机的财务危机预警模型  

A Model Based on Support Vector Machine for Early Warning Financial Crisis

作　　者：吴冬梅[1] 朱俊[1] 庄新田[1] 杨霖[1] 

机构地区：[1]东北大学工商管理学院,辽宁沈阳110004

出　　处：《东北大学学报（自然科学版）》2010年第4期601-604,共4页Journal of Northeastern University(Natural Science)

基　　金：教育部高等学校博士学科点专项科研基金资助项目(20060145001)

摘　　要：首先利用因子分析、均值检验和相关性分析分别对财务指标和公司治理变量进行筛选,得到具有代表性的指标变量,然后利用支持向量机方法进行实证分析.研究结果表明,支持向量机模型对于企业破产风险有较强的预测能力.通过与财务指标下的模型结果进行比较,发现引入公司治理变量(流通股比例、第一大股东持股比例和股权集中度)后,模型的预测能力更强,该方法具有一定的实际应用价值.Financial indicators and corporate governance variables were sieved separately to get representative variables via factor analysis,mean value test and correlation analysis.Then,an empirical analysis was done by support vector machine（SVM）.The results showed that the SVM model is superior in predicting the financial bankruptcy risk to other methods.Comparing the SVM model with the model based on financial indicators,it is found that the model introducing corporate governance variables in it is more predictable,where the variables include the proportions of circulating shares,shares held by the biggest shareholders and share ownership concentration.This method is worthy of practical applications to a certain extent.

关 键 词：支持向量机 因子分析 财务危机 预警 公司治理 

分 类 号：F830.9[经济管理—金融学]