基于BP神经网络模型与DEA模型的中国上市公司利润操纵研究被引量：11

Researches on the Problem of Profit Manipulation in Chinese Listed Corporations based on the BP Neural Network Model

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摘要本文从CCER数据库中的上市公司违法违规数据库取得2006-2009年利润操纵上市公司样本,根据上市公司关键财务数据,构建配对样品组。文章运用粗糙集简化利润操纵的识别指标,通过蒙特卡洛模拟,提出基于BP神经网络模型的中国上市公司利润操纵的识别模型。本研究还引入DEA效率指标,建立改进的中国上市公司利润操纵识别模型,有效降低模型的第二类错误,从而将模型的正判率从71.43%提高到85.71%。 In this paper, listed companies with profit manipulation are collected from the illegal database in CCER database in 2006-2009. Then matched sample groups are established based on the key financial data. By using the rough set theory, indicators of profit manipulation are simplified. We establish a BP neural network model by using Matlab program for the first time. Besides, this paper also uses DEA efficient index to establish an improved model of Chinese listed companies to recognize profit manipulation. The second type of error of the model is reduced and the correct rate of the model is successfully improved from 71.43% to 85.71%.

作者李双杰陈星星

机构地区北京工业大学经济与管理学院中国社会科学院数量经济与技术经济研究所

出处《数理统计与管理》 CSSCI 北大核心 2013年第3期440-451,共12页 Journal of Applied Statistics and Management

基金 2012年度中国社会科学院青年科研启动基金项目的资助

关键词上市公司利润操纵 BP神经网络 DEA模型 listed company, profit manipulation, BP neural network, DEA model

分类号 F224.0 [经济管理—国民经济] O212 [理学—概率论与数理统计]

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