摘要
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。其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。
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, and 76 companies are used as testing samples. The study indicates that compared with previous research that do not differentiate industry, BP fields financial crisis warning model is more accurate in forecasting, provide a useful tool for investors and regulaters. So BP is a relatively good method for analyzing and forecasting financial conditions, with wide applying area and high value of popularizing.
出处
《山东工商学院学报》
2006年第4期56-61,共6页
Journal of Shandong Technology and Business University
关键词
财务预警
人工神经网络
制造业上市公司
预警模型
financial warning
artificial neural network
manufacturing listed company
warning model
