[1]赵梓伊,赵自强,计晓静.基于阈值检验的财务造假预测——基于中国上市公司的数据分析[J].南京师范大学学报(工程技术版),2017,17(02):081.[doi:10.3969/j.issn.1672-1292.2017.02.013]
　Zhao Ziyi,Zhao Ziqiang,Ji Xiaojing.Prediction of Financial Fraud Based on Threshold Test—A Case Study of Listing Corporation in China[J].Journal of Nanjing Normal University(Engineering and Technology),2017,17(02):081.[doi:10.3969/j.issn.1672-1292.2017.02.013]
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基于阈值检验的财务造假预测——基于中国上市公司的数据分析
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南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
17卷
期数:
2017年02期
页码:
081
栏目:
金融工程
出版日期:
2017-06-30

文章信息/Info

Title:
Prediction of Financial Fraud Based on Threshold Test—A Case Study of Listing Corporation in China
文章编号:
1672-1292(2017)02-0081-06
作者:
赵梓伊; 赵自强; 计晓静
南京师范大学金陵女子学院,江苏 南京 210023
Author(s):
Zhao Ziyi; Zhao Ziqiang; Ji Xiaojing
Ginling College,Nanjing Normal University,Nanjing 210023,China
关键词:
预测模型; 阈值检验; 财务造假
Keywords:
predictive model; threshold test; financial fraud
分类号:
F273.1
DOI:
10.3969/j.issn.1672-1292.2017.02.013
文献标志码:
A
摘要:
在大量参考国内外学者对造假公司预测研究的基础上,本文以1993-2012年沪深交易所上市并被发现舞弊的191家公司为样本,并选取61家正常公司作为对比分析. 根据GONE理论来挑选具有中国上市公司独特发展背景的11个新指标,并以Benish的M模型为基础建立了更适合中国市场的新模型. 通过二元逻辑回归法进行筛选,发现公司规模、经营活动现金流比例、资产负债率、是否亏损等4个指标显著性最强,对舞弊公司的影响较大. 借助阈值和ROC检验工具可知本文建立的新模型不仅只是在指标上适用性强,在辨别造假公司上确实也要优于M和F模型,对于多个样本进行模型检验时发现第一类错误率更低,总体准确率有所提升,更适用于在中国资本市场下的应用.
Abstract:
On the basis of referring to a large number of research about financial fraud prediction made by domestic and foreign scholars,this paper takes the listed and found to be fraudulent companies which are in Shanghai and Shenzhen Stock Exchange during 1993-2012 as a sample,selects 11 new indicators with Chinese listed companies development background according to the theory of GONE,and bases on M model by Benish as the base to construct the new model. We screen indexes by logistic regression and finally find that the four indexes had the higher significance. They are company size,Operating cash flow ratio,asset liability ratio and whether losses. With the help of threshold and ROC test tools,it can be known that the new model not only is stronger in the indexes,but also better to distinguish fake company than M and F model. The simulation test of many samples show that type I error rates are lower,that an overall accuracy has improved,and that it is more suitable for application in China’s capital market.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2016-11-01.
基金项目:江苏省社会科学基金(14GLB004).
通讯联系人:赵自强,博士,教授,研究方向:金融市场研究. E-mail:1416511372@qq.com
更新日期/Last Update: 2017-06-30