财务报告舞弊识别的实证研究  

The Empirical Study of Financial Reporting Fraud

作　　者：王雅[1] 袁泉[1] 

机构地区：[1]兰州交通大学经济管理学院,甘肃兰州730070

出　　处：《兰州交通大学学报》2013年第5期68-70,共3页Journal of Lanzhou Jiaotong University

摘　　要：随着舞弊手段日趋隐蔽,需要建立一个快速有效的识别模型。本文选取了24个相关指标作为解释变量,选取了72家财务报告舞弊上市公司作为样本。首先建立Logistic回归模型,模型的判断率达到了71.7%。然后将Logistic回归得到的7个解释变量,用运到BP神经网络模型之中,使判别率达到87.1%,高于出了16%。说明BP神经网络的总体识别率更高。With the increasing concealment for fraud ways, a rapid and efficient recognition model need to be established. In this paper,24 relative indicators are selected as explanatory variables;72 China＇s list compa- nies which had financial reporting fraud are selected as samples. Firstly, a logistic regression model is built, and the recognition rate of this model is 71.7 %. Seven explanatory variables from logistic regression is applied to BP network model. The recognition rae get to 87.1% ,which is 16% higher than the logistic regression model. It indicates that the general recognition rate of BP neural network model is better.

关 键 词：财务报告 舞弊BP神经网络 LOGISTIC回归 

分 类 号：F231.6[经济管理—会计学]