【作者】 张根明； 向晓骥； 王殊伟；

【Author】 ZHANG Gen-ming, XIANG Xiao-ji, WANG Shu-wei ( School of Business Central South University,Changsha 410083 ,China; School of Physics Central South University,Changsha 410083 ,China)

【机构】 中南大学商学院； 中南大学信息物理学院；

【摘要】 文章采用BP神经网络方法,以263家制造业上市公司的截面财务指标作为学习样本,并使用76家制造业上市公司作为检验样本,建立了制造业上市公司财务预警模型。研究结果表明:与没有区分行业的通用预警模型相比,分行业的BP神经网络财务预警模型的预测精度有了较大提高,为广大投资者和监管机构预测公司财务状况提供了可靠的依据。BP神经网络在分析和研究我国上市公司的财务状况方面,具有广泛的应用前景。更多还原

【Abstract】 The paper uses the BP artificial neural network to establish a financial crisis warning model. The model consists of the cross section financial indexes of 263 listed companies in the manufacture industry as study samples, in which 76 companies are used as testing samples. The study indicates that compared with previous research that does not differentiate industry, BP fields financial crisis warning model is more accurate in forecasting, provides a useful tool for investors and regulators. So BP is a relatively good method for analyzing and forecasting financial conditions with wide application area and high value of popularization.更多还原